lxmwust

3D-Unet--Tensorflow

3D Unet for Isointense Infant Brain Image Segmentation

3D_DenseSeg

The implementation of 3D_DenseSeg for infant brain MRI segmentation

3Dunet_abdomen_cascade

ACT

Real-time 'Actor-Critic' tracking

AD3DMIL

Attention Based Deep 3D Multiple Instance Learning

AdelaiDet

AdelaiDet is an open source toolbox for multiple instance-level detection and recognition tasks.

adn

ADN: Artifact Disentanglement Network for Unsupervised Metal Artifact Reduction

ADVENT

Adversarial Entropy Minimization for Domain Adaptation in Semantic Segmentation

Nuclei_Segmentation_Experiments_Demo

Overlapping nuclei segmentation using Deep Interval-Masker-Aware Networks and Marker-controlled Watershed

os-workbench

NJU 操作系统: 设计与实现

lxmwust/os-workbench

NJU 操作系统: 设计与实现

lxmwust/AngioNet

Semantic segmentation network for X-ray angiography images, based on Deeplabv3+

lxmwust/Awesome-Diffusion-Models

A collection of resources and papers on Diffusion Models

lxmwust/CA-Net

Code for Comprehensive Attention Convolutional Neural Networks for Explainable Medical Image Segmentation.

lxmwust/CE-Net

lxmwust/ContrastiveSeg

ICCV2021 (Oral) - Exploring Cross-Image Pixel Contrast for Semantic Segmentation

lxmwust/CoraNet

lxmwust/CS-Net

lxmwust/D-UNet

lxmwust/DeepAtlas

Joint Semi-supervised Learning of Image Registration and Segmentation

lxmwust/DeepAttnMISL

Contains codes of DeepAttnMISL in MEDIA'20

lxmwust/DeepSeeNet

:eyes: DeepSeeNet is a deep learning framework for classifying patient-based age-related macular degeneration severity in retinal color fundus photographs.

lxmwust/domain_specific_cl

Code for NeurIPS 2020 article "Contrastive learning of global and local features for medical image segmentation with limited annotations"

lxmwust/GALD-DGCNet

Source code and models GALD net (BMVC-2019)and Dual-Seg Net (BMVC-2019)

lxmwust/GFS-Seg

The official implementation of Generalized Few-shot Semantic Segmentation (CVPR 2022)

lxmwust/GLIA-Net

A segmentation network for intracranial aneurysm on CTA images using pytorch

lxmwust/Grad-CAM.pytorch

pytorch实现Grad-CAM和Grad-CAM++,可以可视化任意分类网络的Class Activation Map (CAM)图,包括自定义的网络;同时也实现了目标检测faster r-cnn和retinanet两个网络的CAM图;欢迎试用、关注并反馈问题...

lxmwust/lens-structure-segmentation

lxmwust/Livelayer-Software

A Semi-Automatic Software Program for Segmentation of Layers and Diabetic Macular Edema in Optical Coherence Tomography Images

lxmwust/MTLC-Net

MTLC-Net

lxmwust/MVTec-Anomaly-Detection

This project proposes an end-to-end framework for semi-supervised Anomaly Detection and Segmentation in images based on Deep Learning.

lxmwust/OCT-Biomarker-Segmentation

Source code: Deep learning framework (RASP-Net) for segmentation and quantification of chorioretinal biomarkers in OCT scans

lxmwust/OCTAve

Implementation for OCTAve: 2D en face Optical Coherence Tomography Angiography Vessel Segmentation in Weakly-Supervised Learning with Locality Augmentation (IEEE Transactions on Biomedical Engineering))

lxmwust/SDV-LOAM

[TPAMI 2023] A cascaded vision-LiDAR odometry and mapping system

lxmwust/SETR

[CVPR 2021] Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers

lxmwust/SimCLR

PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations by T. Chen et al.

lxmwust/SimCLR-1

PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations

lxmwust/springcloud-config

lxmwust/SSL4MIS

Semi Supervised Learning for Medical Image Segmentation, a collection of literature reviews and code implementations.

lxmwust/Unsupervised_Anomaly_Detection_Brain_MRI

Autoencoders for Unsupervised Anomaly Segmentation in Brain MR Images: A Comparative Study