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Scalable Instance Segmentation using PyTorch & PyTorch Lightning.
StarDist - Object Detection with Star-convex Shapes
数据可视化, 数据挖掘, 数据处理 ETL分析
(NeurIPS 2022 CellSeg Challenge - 1st Winner) Open source code for "MEDIAR: Harmony of Data-Centric and Model-Centric for Multi-Modality Microscopy"
HiFormer: Hierarchical Multi-scale Representations Using Transformers for Medical Image Segmentation (WACV 2023)
Official and maintained implementation of the paper "Attention-Based Transformers for Instance Segmentation of Cells in Microstructures" [BIBM 2020].
Encoder-Decoder Cell and Nuclei segmentation models
a cutting-edge cell segmentation model specifically designed for single-molecule resolved spatial omics datasets. It addresses the challenge of accurately segmenting individual cells in complex imaging datasets, leveraging a unique approach based on graph neural networks (GNNs).
A Hybrid CNN-Transformer Architecture for Precise Medical Image Segmentation
Train torchvision's MaskRCNN model using the ConvNeXt architecture as the backbone network.
A style-aware deep learning model for adaptive cell instance segmentation by contrastive fine-tuning.