Papers Polyp Segmentation
“Polyp Segmentation” 태그가 달린 논문 58편 · 필터 해제
Cross-Model Agreement as a Deployment-Time Reliability Signal for Automatic Polyp Segmentation
In real-time colonoscopy, ground-truth annotations are unavailable at inference, so polyp segmentation models can fail silently. We propose Referee-Based Quality Estimation (RBQE), a reference-free framework measuring ag…
Polyp SegmentationCSG-Mamba: A Convolutional Scoring Gating Vision State Space Network for Endoscopic Polyp Segmentation
Accurate polyp segmentation is critical for computer-aided colonoscopy, yet endoscopic images often contain low-contrast boundaries, mucosal texture interference, specular highlights, and device-dependent appearance shif…
Long-range modelingPolyp SegmentationMetrics or Mirage? An Audit of Evaluation Inconsistencies in Colonoscopy Polyp Segmentation Benchmarks
Progress in colonoscopy polyp segmentation is routinely reported through leaderboard comparisons on a small set of public benchmarks. We argue that this apparent progress is difficult to verify: a systematic audit of \te…
Polyp SegmentationRIGS-Refiner: Risk-Guided Recursive Refinement in Prediction Space for Colonoscopy Polyp Segmentation
Post-refinement can improve colonoscopy segmentation after host inference, but many designs still rely on extra correction heads or multi-stage pipelines with non-negligible parameter or computational cost. For polyp seg…
Polyp SegmentationLightweight Polyp Segmentation via a Gain-Aware Prediction-Space Recursive Controller
While lightweight polyp segmentation is highly desirable for low-cost deployment, reported performance gains often stem from upgraded backbone encoders, complex decoders, or heavy refinement branches. Consequently, it re…
Polyp SegmentationGEN-Guard: Correcting Generalization Failures for Deployable Federated Surgical AI
Federated Learning (FL) in surgical video AI enables collaborative model training without sharing sensitive data. However, standard evaluation practices - selecting the "best" global model based only on validation data f…
Surgical phase recognitionZero-shot GeneralizationFederated LearningPolyp SegmentationEnabling Real-Time Point-of-Care Ultrasound Segmentation: A GPU-Free Deployment in Resource-Limited Settings
Ultrasound imaging is the most widely adopted medical modality globally due to its low cost and portability, yet artificial intelligence (AI) deployment remains constrained by reliance on GPU-accelerated models, creating…
Polyp SegmentationPatch-MoE Mamba: A Patch-Ordered Mixture-of-Experts State Space Architecture for Medical Image Segmentation
CNN- and Transformer-based architectures have achieved strong performance in medical image segmentation, but CNNs are limited in modeling long-range dependencies, while Transformers often suffer from quadratic computatio…
Medical Image SegmentationSkin Lesion SegmentationPolyp SegmentationDepthPolyp: Pseudo-Depth Guided Lightweight Segmentation for Real-Time Colonoscopy
Accurate polyp segmentation in colonoscopy is essential for early colorectal cancer detection, yet real-world clinical environments pose persistent challenges such as motion blur, specular reflections, and illumination i…
Multi-Task LearningPolyp SegmentationRIDE: Retinex-Informed Decoupling for Exposing Concealed Objects
Concealed Object Segmentation (COS) encompasses a family of dense-prediction tasks, including camouflaged object detection, polyp segmentation, transparent object detection, and industrial defect inspection, where target…
Object SegmentationPolyp SegmentationObject DetectionMedCore: Boundary-Preserving Medical Core Pruning for MedSAM
Medical segmentation foundation models such as SAM and MedSAM provide strong prompt-driven segmentation, but their image encoders are still too large for many clinical settings. Compression is also risky in medicine beca…
Polyp SegmentationWhen To Adapt? Adapting the Model or Data in Federated Medical Imaging
Federated learning enables collaborative model training across medical institutions without sharing raw data, but its performance is often limited by domain heterogeneity across clients. Existing approaches to address th…
Federated LearningPolyp SegmentationTumor SegmentationSharpening Lightweight Models for Generalized Polyp Segmentation: A Boundary Guided Distillation from Foundation Models
Automated polyp segmentation is critical for early colorectal cancer detection and its prevention, yet remains challenging due to weak boundaries, large appearance variations, and limited annotated data. Lightweight segm…
Polyp SegmentationASGNet: Adaptive Spectrum Guidance Network for Automatic Polyp Segmentation
Early identification and removal of polyps can reduce the risk of developing colorectal cancer. However, the diverse morphologies, complex backgrounds and often concealed nature of polyps make polyp segmentation in colon…
Polyp SegmentationIP-SAM: Rethinking Prompt-Conditioned Segmentation for Prompt-Absent Deployment
Prompt-conditioned foundation segmenters have emerged as a dominant paradigm for image segmentation, where explicit spatial prompts(e.g., points, boxes, masks) guide mask decoding. However, many real-world deployments re…
Polyp SegmentationImage SegmentationObject DetectionRPG-SAM: Reliability-Weighted Prototypes and Geometric Adaptive Threshold Selection for Training-Free One-Shot Polyp Segmentation
Training-free one-shot segmentation offers a scalable alternative to expert annotations where knowledge is often transferred from support images and foundation models. But existing methods often treat all pixels in suppo…
One-Shot SegmentationPolyp SegmentationPolyp Segmentation Using Wavelet-Based Cross-Band Integration for Enhanced Boundary Representation
Accurate polyp segmentation is essential for early colorectal cancer detection, yet achieving reliable boundary localization remains challenging due to low mucosal contrast, uneven illumination, and color similarity betw…
Polyp SegmentationGRAFNet: Multiscale Retinal Processing via Guided Cortical Attention Feedback for Enhancing Medical Image Polyp Segmentation
Accurate polyp segmentation in colonoscopy is essential for cancer prevention but remains challenging due to: (1) high morphological variability (from flat to protruding lesions), (2) strong visual similarity to normal s…
Polyp SegmentationSurgMotion: A Video-Native Foundation Model for Universal Understanding of Surgical Videos
While foundation models have advanced surgical video analysis, current approaches rely predominantly on pixel-level reconstruction objectives that waste model capacity on low-level visual details, such as smoke, specular…
Action Triplet RecognitionPolyp SegmentationDepth EstimationEnabling Real-Time Colonoscopic Polyp Segmentation on Commodity CPUs via Ultra-Lightweight Architecture
Real-time polyp segmentation is essential for early colorectal cancer detection, yet clinical deployment remains blocked by GPU dependency. We introduce the UltraSeg family, a set of CPU-native segmentation models operat…
Polyp Segmentation