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Image Segmentation

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하위 태스크: 1
평가표: 13
보존된 평가 기록: 34

Image Segmentation is a computer vision task that involves dividing an image into multiple segments or regions, each of which corresponds to a different object or part of an object. The goal of image segmentation is to assign a unique label or category to each pixel in the image, so that pixels with similar attributes are grouped together.

코드

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

https://github.com/medicl-vu/colossal

공식 코드

COLosSAL: A Benchmark for Cold-start Active Learning for 3D Medical Image Segmentation

https://github.com/medicl-vu/promise

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Promise:Prompt-driven 3D Medical Image Segmentation Using Pretrained Image Foundation Models

https://github.com/medicl-vu/variability

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Assessing Test-time Variability for Interactive 3D Medical Image Segmentation with Diverse Point Prompts

https://github.com/medimair/brain-mri-processing-pipeline

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Negligible effect of brain MRI data preprocessing for tumor segmentation

https://github.com/meituan-automl/visionllama

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VisionLLaMA: A Unified LLaMA Backbone for Vision Tasks

https://github.com/melinphd/taal

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TAAL: Test-time Augmentation for Active Learning in Medical Image Segmentation

https://github.com/menggerSherry/Trans_Fusion_Net

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Exploiting full Resolution Feature Context for Liver Tumor and Vessel Segmentation via Integrate Framework: Application to Liver Tumor and Vessel 3D Reconstruction under embedded microprocessor

https://github.com/mengqi-lei/condseg

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ConDSeg: A General Medical Image Segmentation Framework via Contrast-Driven Feature Enhancement

https://github.com/mengyunq/cheart

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CHeart: A Conditional Spatio-Temporal Generative Model for Cardiac Anatomy

https://github.com/mengyuwang826/segrefiner

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SegRefiner: Towards Model-Agnostic Segmentation Refinement with Discrete Diffusion Process

https://github.com/merantix/acosp

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Auto-Compressing Subset Pruning for Semantic Image Segmentation

https://github.com/merantix/mxlabs-daain

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DAAIN: Detection of Anomalous and Adversarial Input using Normalizing Flows

https://github.com/metamedseg/Code

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MetaMedSeg: Volumetric Meta-learning for Few-Shot Organ Segmentation

https://github.com/mfigurnov/sact

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Spatially Adaptive Computation Time for Residual Networks

https://github.com/mhashas/Exploiting-Temporality-For-Semi-Supervised-Video-Segmentation

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Exploiting Temporality for Semi-Supervised Video Segmentation

https://github.com/mi2datalab/swinsmt

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Swin SMT: Global Sequential Modeling in 3D Medical Image Segmentation

https://github.com/miagrouput/augmentations-for-the-unknown

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Data-Agnostic Augmentations for Unknown Variations: Out-of-Distribution Generalisation in MRI Segmentation

https://github.com/mic-dkfz/multitalent

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MultiTalent: A Multi-Dataset Approach to Medical Image Segmentation

https://github.com/michaelofsbu/spatialcorrection

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Learning to Segment from Noisy Annotations: A Spatial Correction Approach

https://github.com/michaelvorndran/inconsistencymasks

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Inconsistency Masks: Removing the Uncertainty from Input-Pseudo-Label Pairs

https://github.com/miclab-unicamp/medical-imaging-tutorial

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Automated computed tomography and magnetic resonance imaging segmentation using deep learning: a beginner's guide

https://github.com/microsoft/X-Decoder

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Generalized Decoding for Pixel, Image, and Language

https://github.com/midas-research/persuasion-advertisements

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Persuasion Strategies in Advertisements

https://github.com/mihirp1998/Slot-TTA

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Test-time Adaptation with Slot-Centric Models

https://github.com/mileswyn/samihs

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SAMIHS: Adaptation of Segment Anything Model for Intracranial Hemorrhage Segmentation

https://github.com/minaghadimiatigh/hyperbolicimagesegmentation

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Hyperbolic Image Segmentation

https://github.com/mindflow-institue/daeformer

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DAE-Former: Dual Attention-guided Efficient Transformer for Medical Image Segmentation

https://github.com/mindflow-institue/ssct

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Self-supervised Semantic Segmentation: Consistency over Transformation

https://github.com/mindflow-institue/transception

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Enhancing Medical Image Segmentation with TransCeption: A Multi-Scale Feature Fusion Approach

https://github.com/mindflow-institue/waveformer

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Unlocking Fine-Grained Details with Wavelet-based High-Frequency Enhancement in Transformers

https://github.com/mingxuangu/few-shot-uda

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Few-shot Unsupervised Domain Adaptation for Multi-modal Cardiac Image Segmentation

https://github.com/minhquanlecs/maskdiff

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MaskDiff: Modeling Mask Distribution with Diffusion Probabilistic Model for Few-Shot Instance Segmentation

https://github.com/minimel/medsamweakfewshotpromptautomation

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Automating MedSAM by Learning Prompts with Weak Few-Shot Supervision

https://github.com/minimel/stochasticbatchal

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Active learning for medical image segmentation with stochastic batches

https://github.com/miquel-espinosa/no-time-to-train

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No time to train! Training-Free Reference-Based Instance Segmentation

https://github.com/miriambellver/refvos

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RefVOS: A Closer Look at Referring Expressions for Video Object Segmentation

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