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import gradio as gr |
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import cv2 |
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import numpy as np |
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import pandas as pd |
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import pydicom |
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import io |
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from PIL import Image |
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import openpyxl |
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from openpyxl.utils import get_column_letter, column_index_from_string |
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import logging |
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import time |
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import traceback |
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from functools import wraps |
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import sys |
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print("Starting imports completed...") |
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logging.basicConfig( |
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level=logging.DEBUG, |
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format='%(asctime)s - %(levelname)s - %(message)s', |
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handlers=[ |
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logging.FileHandler('dicom_analyzer_debug.log'), |
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logging.StreamHandler(sys.stdout) |
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] |
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) |
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logger = logging.getLogger(__name__) |
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def debug_decorator(func): |
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@wraps(func) |
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def wrapper(*args, **kwargs): |
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logger.debug(f"Entering {func.__name__}") |
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start_time = time.time() |
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try: |
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result = func(*args, **kwargs) |
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logger.debug(f"Function {func.__name__} completed successfully") |
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return result |
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except Exception as e: |
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logger.error(f"Error in {func.__name__}: {str(e)}") |
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logger.error(traceback.format_exc()) |
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raise |
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finally: |
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end_time = time.time() |
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logger.debug(f"Execution time: {end_time - start_time:.4f} seconds") |
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return wrapper |
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class DicomAnalyzer: |
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def __init__(self): |
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self.results = [] |
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self.circle_diameter = 9.0 |
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self.zoom_factor = 1.0 |
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self.current_image = None |
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self.dicom_data = None |
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self.display_image = None |
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self.marks = [] |
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self.original_image = None |
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self.original_display = None |
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self.pan_x = 0 |
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self.pan_y = 0 |
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self.max_pan_x = 0 |
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self.max_pan_y = 0 |
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self.CIRCLE_COLOR = (0, 255, 255) |
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self.SMALL_CIRCLES_COLOR = (255, 255, 255) |
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print("DicomAnalyzer initialized...") |
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def save_results(self): |
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try: |
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if not self.results: |
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logger.warning("Attempted to save with no results") |
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return None, "No results to save" |
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df = pd.DataFrame(self.results) |
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columns_order = ['Area (mm²)', 'Mean', 'StdDev', 'Min', 'Max', 'Point'] |
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df = df[columns_order] |
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timestamp = time.strftime("%Y%m%d_%H%M%S") |
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output_file = f"analysis_results_{timestamp}.xlsx" |
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with pd.ExcelWriter(output_file, engine='openpyxl') as writer: |
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df.to_excel(writer, index=False, sheet_name='Results') |
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worksheet = writer.sheets['Results'] |
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for idx, col in enumerate(df.columns): |
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max_length = max( |
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df[col].astype(str).apply(len).max(), |
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len(str(col)) |
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) + 2 |
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worksheet.column_dimensions[get_column_letter(idx + 1)].width = max_length |
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logger.info(f"Results saved successfully to {output_file}") |
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return output_file, f"Results saved successfully to {output_file}" |
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except Exception as e: |
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error_msg = f"Error saving results: {str(e)}" |
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logger.error(error_msg) |
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logger.error(traceback.format_exc()) |
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return None, error_msg |
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def reset_all(self, image): |
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self.results = [] |
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self.marks = [] |
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self.reset_view() |
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return self.update_display(), "All data has been reset" |
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def load_dicom(self, file): |
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try: |
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if file is None: |
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return None, "No file uploaded" |
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if hasattr(file, 'name'): |
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dicom_data = pydicom.dcmread(file.name) |
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else: |
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dicom_data = pydicom.dcmread(file) |
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image = dicom_data.pixel_array.astype(np.float32) |
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self.original_image = image.copy() |
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rescale_slope = getattr(dicom_data, 'RescaleSlope', 1) |
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rescale_intercept = getattr(dicom_data, 'RescaleIntercept', 0) |
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image = (image * rescale_slope) + rescale_intercept |
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self.current_image = image |
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self.dicom_data = dicom_data |
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self.display_image = self.normalize_image(image) |
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self.original_display = self.display_image.copy() |
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self.reset_all(None) |
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print("DICOM file loaded successfully") |
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return self.display_image, "DICOM file loaded successfully" |
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except Exception as e: |
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print(f"Error loading DICOM file: {str(e)}") |
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return None, f"Error loading DICOM file: {str(e)}" |
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def normalize_image(self, image): |
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try: |
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normalized = cv2.normalize( |
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image, |
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None, |
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alpha=0, |
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beta=255, |
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norm_type=cv2.NORM_MINMAX, |
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dtype=cv2.CV_8U |
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) |
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if len(normalized.shape) == 2: |
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normalized = cv2.cvtColor(normalized, cv2.COLOR_GRAY2BGR) |
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return normalized |
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except Exception as e: |
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print(f"Error normalizing image: {str(e)}") |
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return None |
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def reset_view(self): |
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self.zoom_factor = 1.0 |
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self.pan_x = 0 |
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self.pan_y = 0 |
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if self.original_display is not None: |
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return self.update_display() |
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return None |
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def zoom_in(self, image): |
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print("Zooming in...") |
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self.zoom_factor = min(20.0, self.zoom_factor + 0.5) |
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return self.update_display() |
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def zoom_out(self, image): |
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print("Zooming out...") |
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self.zoom_factor = max(1.0, self.zoom_factor - 0.5) |
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return self.update_display() |
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def handle_keyboard(self, key): |
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try: |
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print(f"Handling key press: {key}") |
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pan_amount = int(10 * self.zoom_factor) |
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if key == 'ArrowLeft': |
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self.pan_x = max(0, self.pan_x - pan_amount) |
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elif key == 'ArrowRight': |
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self.pan_x = min(self.max_pan_x, self.pan_x + pan_amount) |
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elif key == 'ArrowUp': |
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self.pan_y = max(0, self.pan_y - pan_amount) |
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elif key == 'ArrowDown': |
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self.pan_y = min(self.max_pan_y, self.pan_y + pan_amount) |
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return self.update_display() |
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except Exception as e: |
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print(f"Error handling keyboard input: {str(e)}") |
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return self.display_image |
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def update_display(self): |
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try: |
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if self.original_display is None: |
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return None |
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height, width = self.original_display.shape[:2] |
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new_height = int(height * self.zoom_factor) |
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new_width = int(width * self.zoom_factor) |
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zoomed = cv2.resize( |
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self.original_display, |
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(new_width, new_height), |
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interpolation=cv2.INTER_CUBIC |
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) |
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zoomed_bgr = cv2.cvtColor(zoomed, cv2.COLOR_RGB2BGR) |
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for x, y, diameter in self.marks: |
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zoomed_x = int(x * self.zoom_factor) |
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zoomed_y = int(y * self.zoom_factor) |
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zoomed_radius = int((diameter / 2.0) * self.zoom_factor) |
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cv2.circle( |
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zoomed_bgr, |
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(zoomed_x, zoomed_y), |
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zoomed_radius, |
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self.CIRCLE_COLOR, |
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1, |
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lineType=cv2.LINE_AA |
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) |
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num_points = 8 |
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for i in range(num_points): |
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angle = 2 * np.pi * i / num_points |
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point_x = int(zoomed_x + zoomed_radius * np.cos(angle)) |
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point_y = int(zoomed_y + zoomed_radius * np.sin(angle)) |
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cv2.circle( |
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zoomed_bgr, |
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(point_x, point_y), |
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1, |
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self.SMALL_CIRCLES_COLOR, |
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-1, |
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lineType=cv2.LINE_AA |
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) |
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zoomed = cv2.cvtColor(zoomed_bgr, cv2.COLOR_BGR2RGB) |
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self.max_pan_x = max(0, new_width - width) |
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self.max_pan_y = max(0, new_height - height) |
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self.pan_x = min(max(0, self.pan_x), self.max_pan_x) |
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self.pan_y = min(max(0, self.pan_y), self.max_pan_y) |
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visible = zoomed[ |
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int(self.pan_y):int(self.pan_y + height), |
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int(self.pan_x):int(self.pan_x + width) |
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] |
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return visible |
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except Exception as e: |
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print(f"Error updating display: {str(e)}") |
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return self.original_display |
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def analyze_roi(self, evt: gr.SelectData): |
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try: |
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if self.current_image is None: |
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return None, "No image loaded" |
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clicked_x = evt.index[0] |
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clicked_y = evt.index[1] |
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x = clicked_x + self.pan_x |
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y = clicked_y + self.pan_y |
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if self.zoom_factor != 1.0: |
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x = x / self.zoom_factor |
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y = y / self.zoom_factor |
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x = int(round(x)) |
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y = int(round(y)) |
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height, width = self.original_image.shape[:2] |
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Y, X = np.ogrid[:height, :width] |
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radius = self.circle_diameter / 2.0 |
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r_squared = radius * radius |
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dx = X - x |
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dy = Y - y |
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dist_squared = dx * dx + dy * dy |
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mask = np.zeros((height, width), dtype=bool) |
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mask[dist_squared <= r_squared] = True |
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roi_pixels = self.original_image[mask] |
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if len(roi_pixels) == 0: |
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return self.display_image, "Error: No pixels selected" |
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pixel_spacing = float(self.dicom_data.PixelSpacing[0]) |
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n_pixels = np.sum(mask) |
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area = n_pixels * (pixel_spacing ** 2) |
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mean_value = np.mean(roi_pixels) |
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std_dev = np.std(roi_pixels, ddof=1) |
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min_val = np.min(roi_pixels) |
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max_val = np.max(roi_pixels) |
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rescale_slope = getattr(self.dicom_data, 'RescaleSlope', 1) |
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rescale_intercept = getattr(self.dicom_data, 'RescaleIntercept', 0) |
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mean_value = (mean_value * rescale_slope) + rescale_intercept |
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std_dev = std_dev * rescale_slope |
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min_val = (min_val * rescale_slope) + rescale_intercept |
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max_val = (max_val * rescale_slope) + rescale_intercept |
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result = { |
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'Area (mm²)': f"{area:.3f}", |
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'Mean': f"{mean_value:.3f}", |
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'StdDev': f"{std_dev:.3f}", |
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'Min': f"{min_val:.3f}", |
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'Max': f"{max_val:.3f}", |
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'Point': f"({x}, {y})" |
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} |
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self.results.append(result) |
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self.marks.append((x, y, self.circle_diameter)) |
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return self.update_display(), self.format_results() |
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except Exception as e: |
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print(f"Error analyzing ROI: {str(e)}") |
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return self.display_image, f"Error analyzing ROI: {str(e)}" |
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def add_formulas_to_template(self, ws, row_pair, col_group, red_font): |
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""" |
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Inserts SNR (first row) and CNR (second row) formulas with IFERROR. |
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""" |
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try: |
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base_col = col_group[1] |
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std_col = col_group[2] |
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row1, row2 = row_pair |
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formula_col = get_column_letter(column_index_from_string(col_group[-1]) + 1) |
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formula_snr = f"=IFERROR({base_col}{row1}/{std_col}{row1},\"\")" |
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cell_snr = ws[f"{formula_col}{row1}"] |
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cell_snr.value = formula_snr |
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cell_snr.font = red_font |
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cell_snr.alignment = openpyxl.styles.Alignment(horizontal='center') |
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formula_cnr = f"=IFERROR(({base_col}{row1}-{base_col}{row2})/{std_col}{row2},\"\")" |
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cell_cnr = ws[f"{formula_col}{row2}"] |
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cell_cnr.value = formula_cnr |
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cell_cnr.font = red_font |
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cell_cnr.alignment = openpyxl.styles.Alignment(horizontal='center') |
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|
|
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logger.debug(f"Added formulas for rows {row1},{row2} in column {formula_col}") |
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except Exception as e: |
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logger.error(f"Error adding formulas: {str(e)}") |
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def save_formatted_results(self, output_path): |
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try: |
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if not self.results: |
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return None, "No results to save" |
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|
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wb = openpyxl.Workbook() |
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ws = wb.active |
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red_font = openpyxl.styles.Font(color="FF0000") |
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|
center_alignment = openpyxl.styles.Alignment(horizontal='center', vertical='center') |
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|
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headers = ['Area', 'Mean', 'StdDev', 'Min', 'Max'] |
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|
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column_groups = [ |
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('B', 'C', 'D', 'E', 'F'), ('H', 'I', 'J', 'K', 'L'), |
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('N', 'O', 'P', 'Q', 'R'), ('T', 'U', 'V', 'W', 'X'), |
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('Z', 'AA', 'AB', 'AC', 'AD'), ('AF', 'AG', 'AH', 'AI', 'AJ'), |
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('AL', 'AM', 'AN', 'AO', 'AP'), ('AR', 'AS', 'AT', 'AU', 'AV'), |
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('AX', 'AY', 'AZ', 'BA', 'BB'), ('BD', 'BE', 'BF', 'BG', 'BH'), |
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('BJ', 'BK', 'BL', 'BM', 'BN'), ('BP', 'BQ', 'BR', 'BS', 'BT'), |
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('BV', 'BW', 'BX', 'BY', 'BZ') |
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] |
|
|
|
|
|
|
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for cols in column_groups: |
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for i, header in enumerate(headers): |
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cell = ws[f"{cols[i]}1"] |
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cell.value = header |
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|
cell.alignment = center_alignment |
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|
|
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row_pairs = [ |
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(2, 3), (5, 6), (8, 9), (11, 12), (14, 15), |
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(17, 18), (20, 21), (23, 24), (26, 27), (29, 30) |
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] |
|
|
|
|
|
phantom_sizes = [ |
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'(7mm)', '(6.5mm)', '(6mm)', '(5.5mm)', '(5mm)', |
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|
'(4.5mm)', '(4mm)', '(3.5mm)', '(3mm)', '(2.5mm)' |
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|
] |
|
|
|
|
|
|
|
|
for i, size in enumerate(phantom_sizes): |
|
|
header_cell = ws.cell(row=row_pairs[i][0]-1, column=1, value=size) |
|
|
header_cell.font = red_font |
|
|
header_cell.alignment = center_alignment |
|
|
|
|
|
|
|
|
result_idx = 0 |
|
|
current_col_group = 0 |
|
|
current_row_pair = 0 |
|
|
|
|
|
while result_idx < len(self.results): |
|
|
if current_row_pair >= len(row_pairs): |
|
|
break |
|
|
|
|
|
cols = column_groups[current_col_group] |
|
|
row1, row2 = row_pairs[current_row_pair] |
|
|
|
|
|
if result_idx < len(self.results): |
|
|
result = self.results[result_idx] |
|
|
self._write_result_to_cells(ws, result, cols, row1) |
|
|
result_idx += 1 |
|
|
|
|
|
if result_idx < len(self.results): |
|
|
result = self.results[result_idx] |
|
|
self._write_result_to_cells(ws, result, cols, row2) |
|
|
result_idx += 1 |
|
|
|
|
|
self.add_formulas_to_template(ws, (row1,row2), cols, red_font) |
|
|
|
|
|
current_col_group += 1 |
|
|
if current_col_group >= len(column_groups): |
|
|
current_col_group = 0 |
|
|
current_row_pair += 1 |
|
|
|
|
|
|
|
|
for cols in column_groups: |
|
|
for col in cols: |
|
|
for row in range(2, 31): |
|
|
cell = ws[f"{col}{row}"] |
|
|
if cell.value is not None: |
|
|
cell.alignment = center_alignment |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
start_row = 35 |
|
|
ws['C35'] = "1-AVG" |
|
|
ws['C35'].alignment = center_alignment |
|
|
|
|
|
ws.merge_cells('D35:E35') |
|
|
ws.merge_cells('F35:G35') |
|
|
ws.merge_cells('H35:I35') |
|
|
|
|
|
headers_avg = { |
|
|
'D35': 'AVG MEAN', |
|
|
'F35': 'AVG STDDEV', |
|
|
'H35': 'AVG CNR' |
|
|
} |
|
|
for c_ref, text_val in headers_avg.items(): |
|
|
ws[c_ref] = text_val |
|
|
ws[c_ref].font = red_font |
|
|
ws[c_ref].alignment = center_alignment |
|
|
|
|
|
|
|
|
phantom_sizes2 = [ |
|
|
'(7.0mm)', '(6.5mm)', '(6.0mm)', '(5.5mm)', '(5.0mm)', |
|
|
'(4.5mm)', '(4.0mm)', '(3.5mm)', '(3.0mm)', '(2.5mm)' |
|
|
] |
|
|
|
|
|
for i, size_label in enumerate(phantom_sizes2): |
|
|
row = start_row + i + 1 |
|
|
|
|
|
ws.merge_cells(f'D{row}:E{row}') |
|
|
ws.merge_cells(f'F{row}:G{row}') |
|
|
ws.merge_cells(f'H{row}:I{row}') |
|
|
|
|
|
c_cell = ws[f'C{row}'] |
|
|
c_cell.value = size_label |
|
|
c_cell.font = red_font |
|
|
c_cell.alignment = center_alignment |
|
|
|
|
|
if i >= len(row_pairs): |
|
|
continue |
|
|
(raw_row1, raw_row2) = row_pairs[i] |
|
|
|
|
|
mean_values = [] |
|
|
stddev_values = [] |
|
|
cnr_cells = [] |
|
|
|
|
|
|
|
|
for group in column_groups: |
|
|
mean_col = group[1] |
|
|
std_col = group[2] |
|
|
|
|
|
|
|
|
m1_val = ws[f"{mean_col}{raw_row1}"].value |
|
|
try: |
|
|
m1_val = float(m1_val) if m1_val not in [None,''] else None |
|
|
except: |
|
|
m1_val = None |
|
|
|
|
|
if m1_val == 0: |
|
|
m1_val = None |
|
|
|
|
|
if m1_val is not None: |
|
|
mean_values.append(m1_val) |
|
|
|
|
|
|
|
|
s1_val = ws[f"{std_col}{raw_row1}"].value |
|
|
try: |
|
|
s1_val = float(s1_val) if s1_val not in [None,''] else None |
|
|
except: |
|
|
s1_val = None |
|
|
if s1_val == 0: |
|
|
s1_val = None |
|
|
|
|
|
if s1_val is not None: |
|
|
stddev_values.append(s1_val) |
|
|
|
|
|
|
|
|
formula_col = get_column_letter(column_index_from_string(group[-1]) + 1) |
|
|
cnr_cell_ref = f"{formula_col}{raw_row2}" |
|
|
|
|
|
|
|
|
|
|
|
mean2_val = ws[f"{mean_col}{raw_row2}"].value |
|
|
std2_val = ws[f"{std_col}{raw_row2}"].value |
|
|
try: |
|
|
mean2_val = float(mean2_val) if mean2_val not in [None,''] else None |
|
|
std2_val = float(std2_val) if std2_val not in [None,''] else None |
|
|
except: |
|
|
mean2_val, std2_val = None, None |
|
|
|
|
|
if mean2_val == 0: |
|
|
mean2_val = None |
|
|
if std2_val == 0: |
|
|
std2_val = None |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
if (m1_val is not None) and (mean2_val is not None) and (std2_val is not None): |
|
|
cnr_cells.append(cnr_cell_ref) |
|
|
|
|
|
|
|
|
final_mean = sum(mean_values)/len(mean_values) if mean_values else None |
|
|
if final_mean is not None: |
|
|
ws[f'D{row}'].value = final_mean |
|
|
ws[f'D{row}'].alignment = center_alignment |
|
|
ws[f'D{row}'].number_format = '0.0000' |
|
|
|
|
|
|
|
|
final_std = sum(stddev_values)/len(stddev_values) if stddev_values else None |
|
|
if final_std is not None: |
|
|
ws[f'F{row}'].value = final_std |
|
|
ws[f'F{row}'].alignment = center_alignment |
|
|
ws[f'F{row}'].number_format = '0.0000' |
|
|
|
|
|
|
|
|
if cnr_cells: |
|
|
formula_avg_cnr = f"=IFERROR(AVERAGE({','.join(cnr_cells)}),\"\")" |
|
|
ws[f'H{row}'].value = formula_avg_cnr |
|
|
ws[f'H{row}'].alignment = center_alignment |
|
|
ws[f'H{row}'].number_format = '0.0000' |
|
|
|
|
|
|
|
|
thin_side = openpyxl.styles.Side(style='thin') |
|
|
border = openpyxl.styles.Border( |
|
|
left=thin_side, right=thin_side, top=thin_side, bottom=thin_side |
|
|
) |
|
|
for r in range(35, 46): |
|
|
for col in ['C','D','E','F','G','H','I']: |
|
|
ws[f"{col}{r}"].border = border |
|
|
|
|
|
wb.save(output_path) |
|
|
return output_path, f"Results saved successfully ({len(self.results)} measurements)" |
|
|
except Exception as e: |
|
|
logger.error(f"Error saving formatted results: {str(e)}") |
|
|
return None, f"Error saving results: {str(e)}" |
|
|
|
|
|
def _write_result_to_cells(self, ws, result, cols, row): |
|
|
center_alignment = openpyxl.styles.Alignment(horizontal='center') |
|
|
|
|
|
value_mapping = { |
|
|
'Area': 'Area (mm²)', |
|
|
'Mean': 'Mean', |
|
|
'StdDev': 'StdDev', |
|
|
'Min': 'Min', |
|
|
'Max': 'Max' |
|
|
} |
|
|
|
|
|
for i, (header, key) in enumerate(value_mapping.items()): |
|
|
cell = ws[f"{cols[i]}{row}"] |
|
|
val = result[key] |
|
|
cell.value = float(val) if val not in ['', None] else '' |
|
|
cell.alignment = center_alignment |
|
|
|
|
|
def format_results(self): |
|
|
if not self.results: |
|
|
return "No measurements yet" |
|
|
df = pd.DataFrame(self.results) |
|
|
columns_order = ['Area (mm²)', 'Mean', 'StdDev', 'Min', 'Max', 'Point'] |
|
|
df = df[columns_order] |
|
|
return df.to_string(index=False) |
|
|
|
|
|
def add_zero_row(self, image): |
|
|
self.results.append({ |
|
|
'Area (mm²)': '0.000', |
|
|
'Mean': '0.000', |
|
|
'StdDev': '0.000', |
|
|
'Min': '0.000', |
|
|
'Max': '0.000', |
|
|
'Point': '(0, 0)' |
|
|
}) |
|
|
return image, self.format_results() |
|
|
|
|
|
def add_two_zero_rows(self, image): |
|
|
for _ in range(2): |
|
|
self.results.append({ |
|
|
'Area (mm²)': '0.000', |
|
|
'Mean': '0.000', |
|
|
'StdDev': '0.000', |
|
|
'Min': '0.000', |
|
|
'Max': '0.000', |
|
|
'Point': '(0, 0)' |
|
|
}) |
|
|
return image, self.format_results() |
|
|
|
|
|
def undo_last(self, image): |
|
|
if not self.results: |
|
|
return self.update_display(), self.format_results() |
|
|
|
|
|
last_result = self.results[-1] |
|
|
is_measurement = (last_result['Point'] != '(0, 0)') |
|
|
self.results.pop() |
|
|
|
|
|
if is_measurement and self.marks: |
|
|
self.marks.pop() |
|
|
|
|
|
return self.update_display(), self.format_results() |
|
|
|
|
|
|
|
|
def create_interface(): |
|
|
print("Creating interface...") |
|
|
analyzer = DicomAnalyzer() |
|
|
|
|
|
with gr.Blocks(css="#image_display { outline: none; }") as interface: |
|
|
gr.Markdown("# DICOM Image Analyzer") |
|
|
|
|
|
with gr.Row(): |
|
|
with gr.Column(): |
|
|
file_input = gr.File(label="Upload DICOM file") |
|
|
diameter_slider = gr.Slider( |
|
|
minimum=1, |
|
|
maximum=20, |
|
|
value=9, |
|
|
step=1, |
|
|
label="ROI Diameter (pixels)" |
|
|
) |
|
|
|
|
|
with gr.Row(): |
|
|
zoom_in_btn = gr.Button("Zoom In (+)") |
|
|
zoom_out_btn = gr.Button("Zoom Out (-)") |
|
|
reset_btn = gr.Button("Reset View") |
|
|
reset_all_btn = gr.Button("Reset All") |
|
|
|
|
|
with gr.Column(): |
|
|
image_display = gr.Image( |
|
|
label="DICOM Image", |
|
|
interactive=True, |
|
|
elem_id="image_display" |
|
|
) |
|
|
|
|
|
with gr.Row(): |
|
|
zero_btn = gr.Button("Add Zero Row") |
|
|
zero2_btn = gr.Button("Add Two Zero Rows") |
|
|
undo_btn = gr.Button("Undo Last") |
|
|
save_btn = gr.Button("Save Results") |
|
|
save_formatted_btn = gr.Button("Save Formatted Results") |
|
|
|
|
|
results_display = gr.Textbox(label="Results", interactive=False) |
|
|
file_output = gr.File(label="Download Results") |
|
|
key_press = gr.Textbox(visible=False, elem_id="key_press") |
|
|
|
|
|
gr.Markdown(""" |
|
|
### Controls: |
|
|
- Use arrow keys to pan when zoomed in. Movement is now larger. |
|
|
- Click points to measure ROI. |
|
|
- Use Zoom In/Out buttons or Reset View to adjust zoom level. |
|
|
- Use Reset All to clear all measurements. |
|
|
- "Save Results": basic Excel with raw data. |
|
|
- "Save Formatted Results": Excel with advanced formatting & formulas. |
|
|
""") |
|
|
|
|
|
def update_diameter(x): |
|
|
analyzer.circle_diameter = float(x) |
|
|
print(f"Diameter updated to: {x}") |
|
|
return f"Diameter set to {x} pixels" |
|
|
|
|
|
def save_formatted(): |
|
|
output_path = "analysis_results_formatted.xlsx" |
|
|
return analyzer.save_formatted_results(output_path) |
|
|
|
|
|
file_input.change( |
|
|
fn=analyzer.load_dicom, |
|
|
inputs=file_input, |
|
|
outputs=[image_display, results_display] |
|
|
) |
|
|
|
|
|
image_display.select( |
|
|
fn=analyzer.analyze_roi, |
|
|
outputs=[image_display, results_display] |
|
|
) |
|
|
|
|
|
diameter_slider.change( |
|
|
fn=update_diameter, |
|
|
inputs=diameter_slider, |
|
|
outputs=gr.Textbox(label="Status") |
|
|
) |
|
|
|
|
|
zoom_in_btn.click( |
|
|
fn=analyzer.zoom_in, |
|
|
inputs=image_display, |
|
|
outputs=image_display, |
|
|
queue=False |
|
|
) |
|
|
|
|
|
zoom_out_btn.click( |
|
|
fn=analyzer.zoom_out, |
|
|
inputs=image_display, |
|
|
outputs=image_display, |
|
|
queue=False |
|
|
) |
|
|
|
|
|
reset_btn.click( |
|
|
fn=analyzer.reset_view, |
|
|
outputs=image_display |
|
|
) |
|
|
|
|
|
reset_all_btn.click( |
|
|
fn=analyzer.reset_all, |
|
|
inputs=image_display, |
|
|
outputs=[image_display, results_display] |
|
|
) |
|
|
|
|
|
key_press.change( |
|
|
fn=analyzer.handle_keyboard, |
|
|
inputs=key_press, |
|
|
outputs=image_display |
|
|
) |
|
|
|
|
|
zero_btn.click( |
|
|
fn=analyzer.add_zero_row, |
|
|
inputs=image_display, |
|
|
outputs=[image_display, results_display] |
|
|
) |
|
|
|
|
|
zero2_btn.click( |
|
|
fn=analyzer.add_two_zero_rows, |
|
|
inputs=image_display, |
|
|
outputs=[image_display, results_display] |
|
|
) |
|
|
|
|
|
undo_btn.click( |
|
|
fn=analyzer.undo_last, |
|
|
inputs=image_display, |
|
|
outputs=[image_display, results_display] |
|
|
) |
|
|
|
|
|
save_btn.click( |
|
|
fn=analyzer.save_results, |
|
|
outputs=[file_output, results_display] |
|
|
) |
|
|
|
|
|
save_formatted_btn.click( |
|
|
fn=save_formatted, |
|
|
outputs=[file_output, results_display] |
|
|
) |
|
|
|
|
|
|
|
|
js = """ |
|
|
<script> |
|
|
document.addEventListener('keydown', function(e) { |
|
|
if (['ArrowUp','ArrowDown','ArrowLeft','ArrowRight'].includes(e.key)) { |
|
|
e.preventDefault(); |
|
|
const el = document.querySelector('#key_press textarea'); |
|
|
if (el) { |
|
|
el.value = e.key; |
|
|
el.dispatchEvent(new Event('input')); |
|
|
setTimeout(() => { |
|
|
el.value = ''; |
|
|
el.dispatchEvent(new Event('input')); |
|
|
}, 100); |
|
|
} |
|
|
} |
|
|
}); |
|
|
</script> |
|
|
""" |
|
|
gr.HTML(js) |
|
|
|
|
|
print("Interface created successfully") |
|
|
return interface |
|
|
|
|
|
|
|
|
if __name__ == "__main__": |
|
|
try: |
|
|
print("Starting application...") |
|
|
interface = create_interface() |
|
|
print("Launching interface...") |
|
|
interface.queue() |
|
|
interface.launch( |
|
|
server_name="0.0.0.0", |
|
|
server_port=7860, |
|
|
share=True, |
|
|
debug=True, |
|
|
show_error=True, |
|
|
quiet=False |
|
|
) |
|
|
except Exception as e: |
|
|
print(f"Error launching application: {str(e)}") |
|
|
logger.error(f"Error launching application: {str(e)}") |
|
|
logger.error(traceback.format_exc()) |
|
|
raise e |
|
|
|