Fig. 1: End-to-end AI architecture for bone marrow aspirate cytology.
From: Automated bone marrow cytology using deep learning to generate a histogram of cell types
In this architecture, initially, our Region of Interest (ROI) detection model is run on unprocessed bone marrow aspirate WSI. A grid is created on an original Whole-Slide Image (WSI) and ROI tiles are selected using ROI detection model. Subsequently, a You-Only-Look-Once (YOLO)-based object detection and classification is run to localize and classify cells in the selected tiles and generate the Integrated Histogram of Cell Types (IHCT).
