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whole slide images

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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/bmirds/wsi-plp

공식 코드

Masked Pre-Training of Transformers for Histology Image Analysis

https://github.com/boyden/pointtransformerfl

공식 코드

Point Transformer with Federated Learning for Predicting Breast Cancer HER2 Status from Hematoxylin and Eosin-Stained Whole Slide Images

https://github.com/bozeklab/Histo-Miner

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Histo-Miner: Deep Learning based Tissue Features Extraction Pipeline from H&E Whole Slide Images of Cutaneous Squamous Cell Carcinoma

https://github.com/bryanwong17/mil-feature-extractor-selection

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Rethinking Pre-Trained Feature Extractor Selection in Multiple Instance Learning for Whole Slide Image Classification

https://github.com/bupt-ai-cz/BALNMP

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Predicting Axillary Lymph Node Metastasis in Early Breast Cancer Using Deep Learning on Primary Tumor Biopsy Slides

https://github.com/caiyu6666/medianomaly

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MedIAnomaly: A comparative study of anomaly detection in medical images

https://github.com/can-can-ya/QPMIL-VL

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Queryable Prototype Multiple Instance Learning with Vision-Language Models for Incremental Whole Slide Image Classification

https://github.com/caodoanh2001/FALFormer

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FALFormer: Feature-aware Landmarks self-attention for Whole-slide Image Classification

https://github.com/cassie07/pathomics

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Pathology-and-genomics Multimodal Transformer for Survival Outcome Prediction

https://github.com/chengjin-git/hmil

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HMIL: Hierarchical Multi-Instance Learning for Fine-Grained Whole Slide Image Classification

https://github.com/chongqingnosubway/pdl

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PDL: Regularizing Multiple Instance Learning with Progressive Dropout Layers

https://github.com/choosehappy/QuickAnnotator

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Quick Annotator: an open-source digital pathology based rapid image annotation tool

https://github.com/chuhan89/wsss-tissue

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Multi-Layer Pseudo-Supervision for Histopathology Tissue Semantic Segmentation using Patch-level Classification Labels

https://github.com/chunyuan1/himt

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Hierarchical Transformer for Survival Prediction Using Multimodality Whole Slide Images and Genomics

https://github.com/code-lukas/medical_image_deidentification

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De-Identification of Medical Imaging Data: A Comprehensive Tool for Ensuring Patient Privacy

https://github.com/computationalpathologygroup/hooknet

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HookNet: multi-resolution convolutional neural networks for semantic segmentation in histopathology whole-slide images

https://github.com/computationalpathologygroup/hvit

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Hierarchical Vision Transformers for Context-Aware Prostate Cancer Grading in Whole Slide Images

https://github.com/cpystan/wsi-caption

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WsiCaption: Multiple Instance Generation of Pathology Reports for Gigapixel Whole-Slide Images

https://github.com/cpystan/wsi-vqa

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WSI-VQA: Interpreting Whole Slide Images by Generative Visual Question Answering

https://github.com/cradleai/LKS-Dataset

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SOS: Selective Objective Switch for Rapid Immunofluorescence Whole Slide Image Classification

https://github.com/craigmyles/surgen-dataset

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SurGen: 1020 H&E-stained Whole Slide Images With Survival and Genetic Markers

https://github.com/cvblab/gleason_grading_cmpb

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Going Deeper through the Gleason Scoring Scale: An Automatic end-to-end System for Histology Prostate Grading and Cribriform Pattern Detection

https://github.com/cvblab/kd_resolution

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Attention to detail: inter-resolution knowledge distillation

https://github.com/cvblab/mitosis-uts

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Attention to detail: inter-resolution knowledge distillation

https://github.com/cvblab/self_learning_wsi_prostate

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Self-learning for weakly supervised Gleason grading of local patterns

https://github.com/cvlab-stonybrook/local_learning_wsi

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Gigapixel Whole-Slide Images Classification using Locally Supervised Learning

https://github.com/cymichael/roi_detection

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Region of Interest Detection in Melanocytic Skin Tumor Whole Slide Images -- Nevus & Melanoma

https://github.com/czzzzzzzzzzzzzzzzz/vgat

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VGAT: A Cancer Survival Analysis Framework Transitioning from Generative Visual Question Answering to Genomic Reconstruction

https://github.com/dazhangyu123/adr

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AEM: Attention Entropy Maximization for Multiple Instance Learning based Whole Slide Image Classification

https://github.com/dazhangyu123/aem

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AEM: Attention Entropy Maximization for Multiple Instance Learning based Whole Slide Image Classification

https://github.com/dbo-dkfz/wsi-calib

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On the calibration of neural networks for histological slide-level classification

https://github.com/dddavid4real/HistGen

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HistGen: Histopathology Report Generation via Local-Global Feature Encoding and Cross-modal Context Interaction

https://github.com/dddavid4real/focus

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FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification

https://github.com/ddrrnn123/casc-ai

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CASC-AI: Consensus-aware Self-corrective AI Agents for Noise Cell Segmentation

https://github.com/ddrrnn123/omni-seg

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An Accelerated Pipeline for Multi-label Renal Pathology Image Segmentation at the Whole Slide Image Level

https://github.com/deepmicroscopy/adaptiveregionselection

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Adaptive Region Selection for Active Learning in Whole Slide Image Semantic Segmentation

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.