Update app.py

app.py

@@ -122,75 +122,76 @@ class DicomAnalyzer:
             print(f"Error handling keyboard input: {str(e)}")
             return self.display_image
 
-    def analyze_roi(self, evt: gr.SelectData):
-        try:
-            if self.current_image is None:
-                return None, "No image loaded"
+def analyze_roi(self, evt: gr.SelectData):
+    try:
+        if self.current_image is None:
+            return None, "No image loaded"
 
-            # Get clicked coordinates
-            clicked_x, clicked_y = evt.index[0], evt.index[1]
-            
-            # Transform coordinates to match ImageJ
-            x = (clicked_x + self.pan_x) / self.zoom_factor
-            y = (clicked_y + self.pan_y) / self.zoom_factor
-            
-            # Get image dimensions
-            height, width = self.current_image.shape[:2]
-            
-            # Create precise circular mask (ImageJ method)
-            y_coords, x_coords = np.ogrid[:height, :width]
-            
-            # ImageJ uses diameter/2 for radius calculation
-            radius = (self.circle_diameter - 1) / 2.0  # Adjust radius calculation
-            
-            # Calculate distances using ImageJ method
-            dist_squared = (x_coords - x)**2 + (y_coords - y)**2
-            mask = dist_squared <= radius**2
-            
-            # Get ROI pixels
-            roi_pixels = self.current_image[mask]
-            
-            if len(roi_pixels) == 0:
-                return self.display_image, "Error: No pixels selected"
+        # Get clicked coordinates
+        clicked_x, clicked_y = evt.index[0], evt.index[1]
+        
+        # Transform coordinates to match ImageJ
+        x = (clicked_x + self.pan_x) / self.zoom_factor
+        y = (clicked_y + self.pan_y) / self.zoom_factor
+        
+        # Get image dimensions
+        height, width = self.current_image.shape[:2]
+        
+        # ImageJ-style circle creation
+        Y, X = np.ogrid[:height, :width]
+        
+        # ImageJ uses a specific method for radius calculation
+        radius = self.circle_diameter / 2.0
+        
+        # Create the circular ROI mask using ImageJ's method
+        # ImageJ considers pixels as 1x1 squares centered on integer coordinates
+        dist_squared = (X - x)**2 + (Y - y)**2
+        mask = dist_squared <= (radius * radius)
+        
+        # Get ROI pixels
+        roi_pixels = self.current_image[mask]
+        
+        if len(roi_pixels) == 0:
+            return self.display_image, "Error: No pixels selected"
 
-            # Get pixel spacing (mm/pixel)
-            pixel_spacing = float(self.dicom_data.PixelSpacing[0])
-            
-            # Calculate area using ImageJ method
-            n_pixels = np.sum(mask)  # Count of pixels in mask
-            area = n_pixels * (pixel_spacing ** 2)
-            
-            # Calculate other statistics
-            mean_value = np.mean(roi_pixels)
-            std_dev = np.std(roi_pixels, ddof=1)  # ImageJ uses n-1
-            min_val = np.min(roi_pixels)
-            max_val = np.max(roi_pixels)
+        # Get pixel spacing (mm/pixel)
+        pixel_spacing = float(self.dicom_data.PixelSpacing[0])
+        
+        # Calculate area exactly as ImageJ does
+        n_pixels = np.sum(mask)  # Total number of pixels in ROI
+        area = n_pixels * (pixel_spacing * pixel_spacing)  # Area in mm²
+        
+        # Calculate other statistics
+        mean_value = np.mean(roi_pixels)
+        std_dev = np.std(roi_pixels, ddof=1)  # ImageJ uses n-1 for standard deviation
+        min_val = np.min(roi_pixels)
+        max_val = np.max(roi_pixels)
 
-            # Store results
-            result = {
-                'Area (mm²)': f"{area:.3f}",
-                'Mean': f"{mean_value:.3f}",
-                'StdDev': f"{std_dev:.3f}",
-                'Min': f"{min_val:.3f}",
-                'Max': f"{max_val:.3f}",
-                'Point': f"({x:.1f}, {y:.1f})"
-            }
-            
-            print(f"ROI Analysis Results:")
-            print(f"Area: {area:.3f} mm²")
-            print(f"Mean: {mean_value:.3f}")
-            print(f"StdDev: {std_dev:.3f}")
-            print(f"Min: {min_val:.3f}")
-            print(f"Max: {max_val:.3f}")
-            print(f"Position: ({x:.1f}, {y:.1f})")
-            
-            self.results.append(result)
-            self.marks.append((x, y, self.circle_diameter))
+        # Store results
+        result = {
+            'Area (mm²)': f"{area:.3f}",
+            'Mean': f"{mean_value:.3f}",
+            'StdDev': f"{std_dev:.3f}",
+            'Min': f"{min_val:.3f}",
+            'Max': f"{max_val:.3f}",
+            'Point': f"({x:.1f}, {y:.1f})"
+        }
+        
+        print(f"ROI Analysis Results:")
+        print(f"Number of pixels: {n_pixels}")
+        print(f"Pixel spacing: {pixel_spacing} mm")
+        print(f"Area: {area:.3f} mm²")
+        print(f"Mean: {mean_value:.3f}")
+        print(f"StdDev: {std_dev:.3f}")
+        print(f"Position: ({x:.1f}, {y:.1f})")
+        
+        self.results.append(result)
+        self.marks.append((x, y, self.circle_diameter))
 
-            return self.update_display(), self.format_results()
-        except Exception as e:
-            print(f"Error analyzing ROI: {str(e)}")
-            return self.display_image, f"Error analyzing ROI: {str(e)}"
+        return self.update_display(), self.format_results()
+    except Exception as e:
+        print(f"Error analyzing ROI: {str(e)}")
+        return self.display_image, f"Error analyzing ROI: {str(e)}"
     def update_display(self):
         try:
             if self.original_display is None: