How AI is Transforming Clinical Pathology – Overview
- AI is changing clinical pathology by automating tasks such as image analysis, data interpretation, and diagnostic decision making.
- AI algorithms can analyze pathology images and identify patterns that may be difficult for human pathologists to discern.
- They can also assist in the interpretation of laboratory test results, helping to identify potential issues and make diagnostic recommendations.
- Additionally, AI can be used to improve the efficiency and accuracy of pathology workflow, including tasks such as tissue sample analysis and slide preparation.
How Our AI solution helped clinical pathology lab?
- Artificial Intelligence has transformed the field of medical image analysis providing a helping hand in clinical decisions.
- With help of the artificial intelligence-based model, pharmaceutical companies, patients, and society are benefited at large with scalable and cost-effective solutions.
- We have teamed up with a startup company in developing an open platform that identifies histology images where the texture, spectral and structural features such as the nucleus with the help of Image processing.
- This solution is integrated with multiple datatypes for increasing the efficiency of analysis and improves success for biomarker development.
- The intent of this project is to train Computer Vision-based model that can classify pathology image tiles as benign or malignant.
- It deals with histology images where the texture, spectral and structural features such as the nucleus are identified with the help of Image processing.
- The structural features such as shape index, compactness, elliptic fit, distance, etc. of the nucleus.
- The spectral features involve finding out the optical density format of the given images and obtaining the stain vectors and intensity for the stains involved in the histology images such as Hematoxylin, Eosin, and Residual.