1. Segmentation of Multiple Myeloma Plasma Cells in Microscopic Images (SegPc-2021)

This challenge was organized as a part of The IEEE International Symposium on Biomedical Imaging (ISBI)-2021 conference. It was a collaborative work of SBILab, IIIT-Delhi and Laboratory Oncology Unit, AIIMS, New-Delhi.

Aim: Segmentation of cells’ (nucleus+cytoplasm) instances from multiple myeloma microscopic images. This challenge is foucssed on cell instance segmentation. The problem is challenging as it involves whole cell (nucleus+cytoplasm) segmentation. Also, cell instance segmentation is challenging when cells are clustered.
[Challenge Website][Challenge Dataset]

2. Classification of Normal vs Malignant Cells in B-ALL White Blood Cancer Microscopic Image (CNMC-19)

This challenges was organized as a part of The IEEE International Symposium on Biomedical Imaging (ISBI)-2019 conference. It was a collaborative work of SBILab, IIIT-Delhi and Laboratory Oncology Unit, AIIMS, New-Delhi.

Aim: Classification of leukemic B-lymphoblast cells from normal B-lymphoid precursors from blood smear microscopic images. In this challenge, a dataset of cells with labels (normal versus malignant) was be provided to train machine learning based classifier to identify normal cells from leukemic blasts (malignant cells). These cells were segmented from the images after stain normalization. The methods developed by participants were compared using weighted F1 performance metric. The leaderboard of this challenge is till open and submssions can be made to evaluate the performance on the test set.
[Challenge Website][Challenge Dataset] [Challenge Proceedings]