Mobiusi/Blood-Sample-Microscopic-Image-Classification-Dataset

Blood Sample Microscopic Image Classification Dataset

Current scientific research in medical testing relies on manual analysis by experts, which is time-consuming and prone to human error. Existing automated analysis systems lack precision when processing different types of blood samples. This dataset aims to establish an efficient deep learning model to enhance the classification and detection of different types of blood cells under the microscope, meeting the needs of rapid medical diagnosis and research. Data collection is conducted using high-resolution microscopes in a standardized laboratory environment to ensure consistency in sample collection. Quality control involves multiple rounds of annotation and consistency checks, ensuring each image is accurately annotated and reviewed by experts. The annotation team consists of professionals with a biomedical background, totaling 20 people. Data preprocessing includes techniques such as image denoising, normalization, and augmentation, stored in JPG format, organized by sample category.

Technical Specifications

Field	Type	Description
file_name	string	File name
quality	string	Resolution
cell_type	string	The type of blood sample cells in the microscopic image, such as red blood cells, white blood cells, etc.
magnification_level	integer	The magnification level used when capturing the microscopic image.
staining_method	string	The staining technique used for blood samples in the microscopic image.
image_quality	string	The clarity or resolution grade of the microscopic image.
artifact_presence	boolean	Indicates whether there are any artifacts or background interferences in the microscopic image.
contrast_level	integer	The intensity of the contrast level in the microscopic image.
color_space	string	The color space used in the microscopic image, such as RGB, CMYK, etc.
focus_level	string	The degree of focus in the microscopic image, indicating if the image is sharp.
image_artifact_type	string	The type of artifacts present in the microscopic image.
region_of_interest	string	Regions in the microscopic image that require focused analysis or attention.

Compliance Statement

Authorization Type	CC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike)
Commercial Use	Requires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and Anonymization	No PII, no real company names, simulated scenarios follow industry standards
Compliance System	Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs

Source & Contact

If you need more dataset details, please visit Mobiusi. or contact us via contact@mobiusi.com