The Multi-modality Cell Segmentation Challenge: Towards Universal Solutions

no code implementations • 10 Aug 2023 • Jun Ma, Ronald Xie, Shamini Ayyadhury, Cheng Ge, Anubha Gupta, Ritu Gupta, Song Gu, Yao Zhang, Gihun Lee, Joonkee Kim, Wei Lou, Haofeng Li, Eric Upschulte, Timo Dickscheid, José Guilherme de Almeida, Yixin Wang, Lin Han, Xin Yang, Marco Labagnara, Vojislav Gligorovski, Maxime Scheder, Sahand Jamal Rahi, Carly Kempster, Alice Pollitt, Leon Espinosa, Tâm Mignot, Jan Moritz Middeke, Jan-Niklas Eckardt, Wangkai Li, Zhaoyang Li, Xiaochen Cai, Bizhe Bai, Noah F. Greenwald, David Van Valen, Erin Weisbart, Beth A. Cimini, Trevor Cheung, Oscar Brück, Gary D. Bader, Bo wang

This benchmark and the improved algorithm offer promising avenues for more accurate and versatile cell analysis in microscopy imaging.

Cell Segmentation Segmentation

SDCT-AuxNet$^θ$: DCT Augmented Stain Deconvolutional CNN with Auxiliary Classifier for Cancer Diagnosis

no code implementations • 30 May 2020 • Shiv Gehlot, Anubha Gupta, Ritu Gupta

However, the development of such a tool for ALL cancer was challenging so far due to the non-availability of a large training dataset.

Decision Making

Heterogeneity Loss to Handle Intersubject and Intrasubject Variability in Cancer

1 code implementation • 6 Mar 2020 • Shubham Goswami, Suril Mehta, Dhruva Sahrawat, Anubha Gupta, Ritu Gupta

We also propose an unorthodox ensemble strategy that helps us in providing improved classification over models trained on 7-folds giving a weighted-$F_1$ score of 95. 26% on unseen (test) subjects' data that are, so far, the best results on the C-NMC 2019 dataset for B-ALL classification.

LeukoNet: DCT-based CNN architecture for the classification of normal versus Leukemic blasts in B-ALL Cancer

no code implementations • 18 Oct 2018 • Simmi Mourya, Sonaal Kant, Pulkit Kumar, Anubha Gupta, Ritu Gupta

Acute lymphoblastic leukemia (ALL) constitutes approximately 25% of the pediatric cancers.

General Classification