- Grand Challenge

Krish Dasgupta

connectwithkrishd

Statistics

Member for 4 years, 1 month

Activity Overview

CAMELYON17

Challenge User

Automated detection and classification of breast cancer metastases in whole-slide images of histological lymph node sections. This task has high clinical relevance and would normally require extensive microscopic assessment by pathologists.

COVID-19 LUNG CT LESION SEGMENTATION CHALLENGE - 2020

Challenge User

This challenge will create the platform to evaluate emerging methods for the segmentation and quantification of lung lesions caused by SARS-CoV-2 infection from CT images.

SegPC-2021

Challenge User

This challenge is positioned towards robust segmentation of cells which is the first stage to build such a tool for plasma cell cancer, namely, Multiple Myeloma (MM), which is a type of blood cancer.

EndoCV2021

Challenge User

Endoscopy Computer Vision Challenge 2021

NODE21

Challenge User

NODE21: generate and detect nodules on chest radiographs

STOIC2021 - COVID-19 AI Challenge

Challenge User

COVID-19 Artificial Intelligence Challenge: automated diagnosis, and prognostic evaluation based on computed tomography

The PI-CAI Challenge

Challenge User

Artificial Intelligence and Radiologists at Prostate Cancer Detection in MRI

CoNIC 2022

Challenge User

Colon Nuclei Identification and Counting Challenge 2022

EndoCV2022

Challenge User

Developing methods for "detection task'' and ''segmentation task'' for endoscopic video sequence data

Parse2022

Challenge User

It is of significant clinical interest to study pulmonary artery structures in the field of medical image analysis. One prerequisite step is to segment pulmonary artery structures from CT with high accuracy and low time-consuming. The segmentation of pulmonary artery structures benefits the quantification of its morphological changes for diagnosis of pulmonary hypertension and thoracic surgery. However, due to the complexity of pulmonary artery topology, automated segmentation of pulmonary artery topology is a challenging task. Besides, the open accessible large-scale CT data with well labeled pulmonary artery are scarce (The large variations of the topological structures from different patients make the annotation an extremely challenging process). The lack of well labeled pulmonary artery hinders the development of automatic pulmonary artery segmentation algorithm. Hence, we try to host the first Pulmonary ARtery SEgmentation challenge in MICCAI 2022 (Named Parse2022) to start a new research topic.

TDSC-ABUS2023

Challenge User

Tumor Detection, Segmentation and Classification Challenge on Automated 3D Breast Ultrasound

INSTANCE2022

Challenge User

The 2022 Intracranial Hemorrhage Segmentation Challenge on Non-Contrast head CT (NCCT)

BCNB

Challenge User

Early Breast Cancer Core-Needle Biopsy WSI Dataset

Cross-Modality Domain Adaptation: Segmentation & Classification

Challenge User

The CrossMoDA 2022 challenge is the second edition of the first large and multi-class medical dataset for unsupervised cross-modality Domain Adaptation.