paper-with-me

Papers Anatomy

“Anatomy” 태그가 달린 논문 1,133편 · 필터 해제

Are Vision Foundation Models Ready for Out-of-the-Box Medical Image Registration?

2025-07-15 · Hanxue Gu, Yaqian Chen, Nicholas Konz, Qihang Li 외

Foundation models, pre-trained on large image datasets and capable of capturing rich feature representations, have recently shown potential for zero-shot image registration. However, their performance has mostly been tes…

AnatomyImage RegistrationMedical Image Registration

PSAT: Pediatric Segmentation Approaches via Adult Augmentations and Transfer Learning

2025-07-08 · Tristan Kirscher, Sylvain Faisan, Xavier Coubez, Loris Barrier 외

Pediatric medical imaging presents unique challenges due to significant anatomical and developmental differences compared to adults. Direct application of segmentation models trained on adult data often yields suboptimal…

AnatomyContinual LearningData AugmentationSegmentation+1

SV-DRR: High-Fidelity Novel View X-Ray Synthesis Using Diffusion Model

2025-07-07 · Chun Xie, Yuichi Yoshii, Itaru Kitahara

X-ray imaging is a rapid and cost-effective tool for visualizing internal human anatomy. While multi-view X-ray imaging provides complementary information that enhances diagnosis, intervention, and education, acquiring i…

AnatomyImage Generation

Causal-SAM-LLM: Large Language Models as Causal Reasoners for Robust Medical Segmentation

2025-07-04 · Tao Tang, Shijie Xu, Yiting Wu, Zhixiang Lu

The clinical utility of deep learning models for medical image segmentation is severely constrained by their inability to generalize to unseen domains. This failure is often rooted in the models learning spurious correla…

AnatomyDisentanglementImage SegmentationMedical Image Segmentation+1

Pose-Star: Anatomy-Aware Editing for Open-World Fashion Images

2025-07-04 · Yuran Dong, Mang Ye

To advance real-world fashion image editing, we analyze existing two-stage pipelines(mask generation followed by diffusion-based editing)which overly prioritize generator optimization while neglecting mask controllabilit…

Anatomy

X-SiT: Inherently Interpretable Surface Vision Transformers for Dementia Diagnosis

2025-06-25 · Fabian Bongratz, Tom Nuno Wolf, Jaume Gual Ramon, Christian Wachinger

Interpretable models are crucial for supporting clinical decision-making, driving advances in their development and application for medical images. However, the nature of 3D volumetric data makes it inherently challengin…

AnatomyDecision MakingDecoder

Volumetric segmentation of muscle compartments using in vivo imaging and architectural validation in human finger flexors

2025-06-25 · Yang Li

Segmenting muscle compartments and measuring their architecture can facilitate movement function assessment, accurate musculoskeletal modeling, and synergy-based electromyogram simulation. Here, we presented a novel meth…

AnatomySegmentation

Learning from Anatomy: Supervised Anatomical Pretraining (SAP) for Improved Metastatic Bone Disease Segmentation in Whole-Body MRI

2025-06-24 · Joris Wuts, Jakub Ceranka, Nicolas Michoux, Frédéric Lecouvet 외

The segmentation of metastatic bone disease (MBD) in whole-body MRI (WB-MRI) is a challenging problem. Due to varying appearances and anatomical locations of lesions, ambiguous boundaries, and severe class imbalance, obt…

AnatomyInductive BiasLesion DetectionSelf-Supervised Learning

Convergent and divergent connectivity patterns of the arcuate fasciculus in macaques and humans

2025-06-24 · Jiahao Huang, Ruifeng Li, Wenwen Yu, Anan Li 외

The organization and connectivity of the arcuate fasciculus (AF) in nonhuman primates remain contentious, especially concerning how its anatomy diverges from that of humans. Here, we combined cross-scale single-neuron tr…

AnatomyDiffusion MRI

CF-Seg: Counterfactuals meet Segmentation

2025-06-19 · Raghav Mehta, Fabio De Sousa Ribeiro, Tian Xia, Melanie Roschewitz 외

Segmenting anatomical structures in medical images plays an important role in the quantitative assessment of various diseases. However, accurate segmentation becomes significantly more challenging in the presence of dise…

AnatomycounterfactualDecision MakingSegmentation

ViT-NeBLa: A Hybrid Vision Transformer and Neural Beer-Lambert Framework for Single-View 3D Reconstruction of Oral Anatomy from Panoramic Radiographs

2025-06-16 · Bikram Keshari Parida, Anusree P. Sunilkumar, Abhijit Sen, Wonsang You

Dental diagnosis relies on two primary imaging modalities: panoramic radiographs (PX) providing 2D oral cavity representations, and Cone-Beam Computed Tomography (CBCT) offering detailed 3D anatomical information. While …

3D ReconstructionAnatomyDiagnosticSingle-View 3D Reconstruction

Improving Prostate Gland Segmenting Using Transformer based Architectures

2025-06-16 · Shatha Abudalou

Inter reader variability and cross site domain shift challenge the automatic segmentation of prostate anatomy using T2 weighted MRI images. This study investigates whether transformer models can retain precision amid suc…

AnatomyComputational Efficiency

On the performance of multi-fidelity and reduced-dimensional neural emulators for inference of physiologic boundary conditions

2025-06-13 · Chloe H. Choi, Andrea Zanoni, Daniele E. Schiavazzi, Alison L. Marsden

Solving inverse problems in cardiovascular modeling is particularly challenging due to the high computational cost of running high-fidelity simulations. In this work, we focus on Bayesian parameter estimation and explore…

AnatomyDimensionality Reductionparameter estimation

Anatomy-Grounded Weakly Supervised Prompt Tuning for Chest X-ray Latent Diffusion Models

2025-06-12 · Konstantinos Vilouras, Ilias Stogiannidis, Junyu Yan, Alison Q. O'Neil 외

Latent Diffusion Models have shown remarkable results in text-guided image synthesis in recent years. In the domain of natural (RGB) images, recent works have shown that such models can be adapted to various vision-langu…

AnatomyImage GenerationPhrase Grounding

Automatic Treatment Planning using Reinforcement Learning for High-dose-rate Prostate Brachytherapy

2025-06-11 · Tonghe Wang, Yining Feng, Xiaofeng Yang

Purpose: In high-dose-rate (HDR) prostate brachytherapy procedures, the pattern of needle placement solely relies on physician experience. We investigated the feasibility of using reinforcement learning (RL) to provide n…

AnatomyReinforcement Learning (RL)

Towards Cross-Subject EMG Pattern Recognition via Dual-Branch Adversarial Feature Disentanglement

2025-06-10 · Xinyue Niu, Akira Furui

Cross-subject electromyography (EMG) pattern recognition faces significant challenges due to inter-subject variability in muscle anatomy, electrode placement, and signal characteristics. Traditional methods rely on subje…

AnatomyDisentanglementElectromyography (EMG)

SakugaFlow: A Stagewise Illustration Framework Emulating the Human Drawing Process and Providing Interactive Tutoring for Novice Drawing Skills

2025-06-10 · Kazuki Kawamura, Jun Rekimoto

While current AI illustration tools can generate high-quality images from text prompts, they rarely reveal the step-by-step procedure that human artists follow. We present SakugaFlow, a four-stage pipeline that pairs dif…

AnatomyImage GenerationLanguage ModelingLanguage Modelling+1

Biologically Inspired Deep Learning Approaches for Fetal Ultrasound Image Classification

2025-06-10 · Rinat Prochii, Elizaveta Dakhova, Pavel Birulin, Maxim Sharaev

Accurate classification of second-trimester fetal ultrasound images remains challenging due to low image quality, high intra-class variability, and significant class imbalance. In this work, we introduce a simple yet pow…

AnatomyDeep Learningimage-classificationImage Classification

Toward Reliable AR-Guided Surgical Navigation: Interactive Deformation Modeling with Data-Driven Biomechanics and Prompts

2025-06-08 · Zheng Han, Jun Zhou, Jialun Pei, Jing Qin 외

In augmented reality (AR)-guided surgical navigation, preoperative organ models are superimposed onto the patient's intraoperative anatomy to visualize critical structures such as vessels and tumors. Accurate deformation…

AnatomyComputational Efficiency

DM-SegNet: Dual-Mamba Architecture for 3D Medical Image Segmentation with Global Context Modeling

2025-06-05 · Hangyu Ji

Accurate 3D medical image segmentation demands architectures capable of reconciling global context modeling with spatial topology preservation. While State Space Models (SSMs) like Mamba show potential for sequence model…

AnatomyBrain Tumor SegmentationDecoderImage Segmentation+7
1–20 / 1,133 다음 →