• Stars
    star
    3
  • Rank 3,946,068 (Top 79 %)
  • Language
    Python
  • Created almost 5 years ago
  • Updated almost 5 years ago

Reviews

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Repository Details

This repository contains an implementation of a deep learning algorithm for tumor segmentation from Whole Slide Images of tissue sections.

More Repositories

1

Nuclei_Segmentation

This is the source code for training and testing our three class CNN algorithm for generalized nuclei segmentation (IEEE TMI paper) using Torch.
Lua
51
star
2

Data-Science-From-Scratch-Python

This repository contains my implementation of the algorithms described in the book "Data Science From Scratch" by Joel Grus. Please scroll down for description of each file.
Jupyter Notebook
9
star
3

CNN-W-SR

Convolutional neural networks for wavelet domain super resolution (implementation of our PR letters paper).
MATLAB
7
star
4

Blogpost-Codes

This repository contains codes for my blogposts focused on machine learning, statistics and data analysis. You can check my work at Medium (https://medium.com/@neeraj.kumar.iitg).
R
1
star
5

Algorithms-and-Data-Structures

This repository contains my implementation of the algorithms discussed in 6.006 CS course of MIT OCW.
Jupyter Notebook
1
star
6

PanCancer_ISDs

This repository contains code and data to reproduce the results of our work on pancancer survival prediction from whole transcriptome data.
R
1
star
7

Prostate-Recurrence-Prediction

Code for convolutional neural network based prostate cancer recurrence prediction (implementation of our SPIE Medical Imaging paper). This algorithm uses CNNs in a regression framework for segmenting nuclei from H&E stained tissue images using a distance transform based approach.
Python
1
star
8

ML_DL_RL_Codes

Implementation of Machine Learning, Deep Learning, Reinforcement Learning, Statistics, and Optimization algorithms in Python. I have organized the codes in respective sub-folders. Ongoing work!
Jupyter Notebook
1
star