histopathology-images
There are 54 repositories under histopathology-images topic.
BMIRDS/deepslide
Code for the Nature Scientific Reports paper "Pathologist-level classification of histologic patterns on resected lung adenocarcinoma slides with deep neural networks." A sliding window framework for classification of high resolution whole-slide images, often microscopy or histopathology images.
maduc7/Histopathology-Datasets
Ressources of histopathology datasets
ChongQingNoSubway/PDL
Code for the paper " PDL: Regularizing Multiple Instance Learning with Progressive Dropout Layers "
gatsby2016/Augmentation-PyTorch-Transforms
Image data augmentation on-the-fly by add new class on transforms in PyTorch and torchvision.
bupt-ai-cz/CAC-UNet-DigestPath2019
1st to MICCAI DigestPath2019 challenge (https://digestpath2019.grand-challenge.org/Home/) on colonoscopy tissue segmentation and classification task. (MICCAI 2019) https://teacher.bupt.edu.cn/zhuchuang/en/index.htm
lyndonchan/hsn_v1
HistoSegNet: Semantic Segmentation of Histological Tissue Type in Whole Slide Images (ICCV 2019)
lxasqjc/Foveation-Segmentation
PyTorch implementation of Foveation for Segmentation of Ultra-High Resolution Images
PhilipChicco/MICCAI2020mil
MICCAI2020. "Multiple Instance Learning with Center Embeddings for Histopathology Image Classification"
Younger330/SemanticEnergyLoss
BIBM2023 regular paper for "Addressing Sparse Annotation: a Novel Semantic Energy Loss for Tumor Cell Detection from Histopathologic Images"
bupt-ai-cz/HSA-NRL
Hard Sample Aware Noise Robust Learning forHistopathology Image Classification
EIDOSLAB/UNITOPATHO
Dataset of 9536 H&E-stained patches for colorectal polyps classification and adenomas grading | ICIP21 https://doi.org/10.1109/ICIP42928.2021.9506198
Zhengyushan/kat
The code for Kernel attention transformer (KAT)
nauyan/NucleiSegmentation
The repository contains a simple pipeline for training Nuclei Segmentation Datasets of Histopathology Images.
andreped/fast-stain-normalization
:star2: GPU-accelerated stain normalization command line tool
open-pathology/awesome-pathology
Awesome List of Digital and Computational Pathology Resources
prakashchhipa/Magnification-Prior-Self-Supervised-Method
Magnification Prior: A Self-Supervised Method for Learning Representations on Breast Cancer Histopathological Images (WACV 2023)
koushikkumarl/capsuleNetwork_cancerclassification
Image classification on lung and colon cancer histopathological images through Capsule Networks or CapsNets.
bupt-ai-cz/Breast-Cancer-Image-Classification-On-WSI-With-Spatial-Correlations
Breast Cancer Image Classification On WSI With Spatial Correlations https://teacher.bupt.edu.cn/zhuchuang/en/index.htm
patolojiatlasi/patolojiatlasi.github.io
Patoloji Atlası
bupt-ai-cz/BreastCancerCNN
https://teacher.bupt.edu.cn/zhuchuang/en/index.htm
juselara1/MLSA
Tensorflow 2.0 implementation of the M-LSA method.
Zhengyushan/lagenet
The code for LAGE-Net
jurgenizer/slidedb
A virtual slide viewer (virtual microscope) for extremely high-resolution histopathology images. Made with Python, Flask and Leaflet.
hbk16/nuclei_detection
The nuclei detection method on histology image proposed in the 2017 paper by Peikari et al.
jaiprakash1824/VLM_Adv_Attack
In the dynamic landscape of medical artificial intelligence, this study explores the vulnerabilities of the Pathology Language-Image Pretraining (PLIP) model, a Vision Language Foundation model, under targeted attacks like PGD adversarial attack.
m-mohsin-zafar/tdc-lc
Official Repository for "Detection of tumour infiltrating lymphocytes in CD3 and CD8 stained histopathological images using a two-phase deep CNN"
erbon7/pcam_analysis
Deep learning analysis of the PCAM dataset
karthik-d/lung-tumor-classification
Deep-learning based classification pipeline for subtyping lung tumors from histology. Study design and codebase to analyze the impact of nucleus segmentation on subtyping.
maduc7/tutorial_transfer_learning_tf
Tutorial to learn how to implement transfer learning in histopathology with Tensorflow 2.0
peterlipan/FoF
The official implementations of our BIBM'24 paper: Focus on Focus: Focus-oriented Representation Learning and Multi-view Cross-modal Alignment for Glioma Grading
raktim-mondol/hist2RNA
Deep learning based method called hist2RNA to predict the expression of genes using digital images of stained tissue samples
shambhavimalik/Histopathologic-Cancer-Detection
The aim is to create an algorithm to identify metastatic cancer in small image patches taken from larger digital pathology scans. We detect cancer by identifying metastatic tissue in histopathologic scans of lymph nodes using Deep Learning. Implemented using Keras.
Anustup900/Histopathology-cancer-image-data-exploration-and-detection-by-deep-learning-VGG-16-CNN
Data Exploration , visualization and deep learning detection as well classification of Histopathology image of cancers by CNN-VGG16 on tcga data set
Aparna-Vijayakumar/Classification-of-Breast-Cancer
Classification of Breast Cancer using Histopathological Images
cansuyalcinn/breast-histopathology-classification
An automated CAD (Computer aided diagnosis) system for the classification of the breast histopathology images. It contains machine learning (feature extraction) and deep learning (transfer learning) pipelines.