- Grand Challenge

Madhu K

madhuk

India
ST.THOMAS COLLEGE OF ENGINEERING AND TECHNOLOGY MATTANNUR
computer science and engineering

Statistics

Member for 3 years
5 challenge submissions

Activity Overview

IDRiD

Challenge User

This challenge evaluates automated techniques for analysis of fundus photographs. We target segmentation of retinal lesions like exudates, microaneurysms, and hemorrhages and detection of the optic disc and fovea. Also, we seek grading of fundus images according to the severity level of DR and DME.

DRIVE

Challenge User

Develop a system to automatically segment vessels in human retina fundus images.

REFUGE

Challenge User

The goal of the Retinal Fundus Glaucoma Challenge (REFUGE) is to evaluate and compare automated algorithms for glaucoma detection and optic disc/cup segmentation on a common dataset of retinal fundus images.

ODIR-2019

Challenge User

北京大学国际眼底图像智能识别竞赛 Peking University International Competition on Ocular Disease Intelligent Recognition

FeTA - Fetal Tissue Annotation Challenge

Challenge User

Fetal Tissue Annotation Challenge

The PI-CAI Challenge

Challenge User

Artificial Intelligence and Radiologists at Prostate Cancer Detection in MRI

Diabetic Retinopathy Analysis Challenge MICCAI2022

Challenge User

Diabetic Retinopathy (DR) lesions segmentation, image quality assessment and classification of proliferatived DR (PDR) and non-PDR in ultra-wide optical coherence tomography angiography mosaic (UW-OCTA-M) images

Foundation Model Prompting for Medical Image Classification

Challenge User

The primary objective of this challenge is to promote the development and evaluation of model adaptation techniques for medical image classification to leverage the existing foundation models.

SegRap 2023

Challenge User

A segmentation challenge with 200 patients (two modalities of CT images, 45 OARs and 2 GTVs).