Classifiers created with Tensorflow 2 and using Fabio Scotti's ALL-IDB (Acute Lymphoblastic Leukemia Image Database for Image Processing) dataset.
A HIAS compatible Acute Lymphoblastic Leukemia classifier trained using Intel Distribution for Python and Intel Optimized Tensorflow. Uses OpenVINO to deploy the model to a Raspberry Pi and Neural Compute Stick 2 for inference on the edge.
Source code for the 2022 CIVEMSA paper "ALLNet: Acute Lymphoblastic Leukemia detection using lightweight convolutional networks"
Source code for the 2021 CIVEMSA paper "Histopathological transfer learning for Acute Lymphoblastic Leukemia detection"
This project is an application designed for complete blood cell counting and automated detection of Acute Lymphoblastic Leukemia (ALL) cells. It works by identifying different types of white blood cells, allowing for the extraction of lymphocyte cells. These cells can then be classified as either normal or indicative of ALL
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