Mingxuan Liu (Arktis2022)

Arktis2022

Geek Repo

Company:Tsinghua University, Department of Biomedical Engineering

Location:Tsinghua University, Haidian District, Beijing

Home Page:https://arktis2022.github.io/

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Mingxuan Liu's starred repositories

Spiking-PhysFormer

Code for "Spiking-PhysFormer: Camera-Based Remote Photoplethysmography with Parallel Spike-driven Transformer"

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ARHNet

ARHNet: Adaptive Region Harmonization for Lesion-aware Augmentation to Improve Segmentation Performance

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Spike-SLR

Source code for "Spike-SLR: Event-based Sign Language Recognition with Efficient Spike-driven Transformer"

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resample

Official implementation of ReSample (https://arxiv.org/abs/2307.08123)

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VMambaMorph

VMambaMorph: a Multi-Modality Deformable Image Registration Framework based on Visual State Space Model with Cross-Scan Module

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Fetal-BE-QA

Code for the paper "A joint brain extraction and image quality assessment framework for fetal brain MRI slices"

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blur-kernel-space-exploring

Exploring Image Deblurring via Blur Kernel Space (CVPR'21)

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atlas-istn

Code release for Atlas-ISTN

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SAM-Med3D

SAM-Med3D: An Efficient General-purpose Promptable Segmentation Model for 3D Volumetric Medical Image

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SpikingResformer

Codes of the paper: SpikingResformer: Bridging ResNet and Vision Transformer in Spiking Neural Networks (CVPR2024)

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EFV_event_classification

[PRCV-2023] Learning Bottleneck Transformer for Event Image-Voxel Feature Fusion based Classification

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Aladdin

Joint Atlas Building and Diffeomorphic Registration Learning with Pairwise Alignment

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conditional_deformation

MICCAI MLMI 2020

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deformable-atlas

Implementation of deformable atlas construction based on differentiable grid sampling and probabilistic programming

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mermaid

Image registration using pytorch

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Atlas-GAN

[ICCV 2021] Generative Adversarial Registration for Improved Conditional Deformable Templates

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voxelmorph

Unsupervised Learning for Image Registration

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DeSAM

The official repository for DeSAM: Decoupled Segment Anything Model for Generalizable Medical Image Segmentation.

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SAMIHS

Code for our Paper "SAMIHS: Adaptation of Segment Anything Model for Efficient Intracranial Hemorrhage Segmentation".

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Segment-Anything-Model-for-Medical-Images

Codes and models for Medical Image Analysis (MIA) 2023 paper. Segment Anything Model for Medical Images?.

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Medical-SAM-Adapter

Adapting Segment Anything Model for Medical Image Segmentation

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SL-animals-DVS-stbp

STBP (Spatio Temporal Back Propagation) implemented on SL-Animals-DVS dataset for training Spiking Neural Networks

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IKD

[KBS 2022] Informative knowledge distillation for image anomaly segmentation

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