causalimages: An R package for performing causal inference with image and image sequence data

Brain Tumor Segmentation using U2-Net Architecture

NOTABLE PROJECTS

My assignments and projects concerned with Biomedical Engineering

H&E ROI-Level and WSI-Level Nuclei Segmentation with HoVer-Net

Intelligent analysis of Biomedical images course

Modified MobileNet-ShuffleNet-GhostNet Network for Lightweight Retinal Vessel Segmentation

Lung Preneoplasia Progression via Pathomics

causalimages: An R package for performing causal inference with image and image sequence data

Fully automatic brain tumour segmentation using Deep 3-D convolutional neural networks

Deep learning for cellular and sub-cellular segmentation made easy.

Keenly optimized obliging picture analysis

An example of easytorch implementation on retinal vessel segmentation.

An entry to the ISBI 2021 Cell Tracking Challenge that uses a Mask R-CNN neural network to detect and segment cells in 2D and 3D microscopy

Fully automatic brain tumor segmentation using the Modified 3DUNet architecture for Brats 2020 Challenge.

Code for brain tumor segmentaion

Term Project on LIDC (Lung Cancer CT Scan) dataset

Cancer Detection from Microscopic Images by Fine-tuning Pre-trained Models ("Inception") for new class labels

Detecting of COVID-19 induced Pneumonia in Chest X-ray Images using using Modified XceptionNet