Latest Medical Imaging Research Papers

The newest Medical Imaging papers from across the field — arXiv, NeurIPS, CVPR, Nature, and more — refreshed daily and ranked by relevance. Distill AI tracks Medical Imaging so you don’t have to: get the standout work delivered to your inbox every morning, with 2-sentence summaries and the option to chat with any paper.

Recent papers

• Perioperative hyperbaric oxygen therapy: mechanisms, evidence, and clinical application.
  Takudzwa Gavaza, Nathanael Matei · PubMed Central · Jan 1, 2027

  Hyperbaric oxygen therapy delivers 100% oxygen at supra-atmospheric pressures, elevating plasma oxygen content and tissue oxygenation above normoxic levels. Once limited to decompression illness, hyperbaric oxygen therapy is gaining recogni…

• Hypoxia-responsive supramolecular systems based on macrocycles and self-assembly structures.
  Farida B. Gabdrakhmanova, Ekaterina S. Churbanova, S. Е. Solovieva, Антипин Игорь Сергеевич · PubMed Central · Jan 1, 2027

  Hypoxia is closely associated with tumor progression, metastasis, therapeutic resistance, and diagnostic challenges. The timely detection of hypoxia in live cancer cells is critical for early cancer diagnosis and for monitoring the effectiv…

• Hydrogen-rich water combined with traditional Chinese medicine compound in the treatment of kidney stones: a randomized controlled prospective clinical trial.
  Yu Yin, Jing Wang, Feng Lian, Yunqing Tang et al. · PubMed Central · Jan 1, 2027

  The formation and development of kidney stones are related to abnormal urine metabolism, oxidative stress and inflammation. Hydrogen-rich water has clear efficacy in antioxidant and improving inflammatory status, while Ye-Shi-Shi-Lin-Formul…

• Unsupervised Deep-learning Methods for Low-dose Computed Tomography Reconstruction
  Ran An · University of Liverpool · Jan 1, 2027

  Computed tomography (CT) has become an indispensable imaging technique in medical diagnostics and industrial applications, owing to its non-invasive nature and high resolution in visualizing object internal structures. While X-ray CT (X-ray…

• DIAGNOSTIC ACCURACY OF MRI IN DETECTING ROTATOR CUFF TEARS TAKING INDIRECT MR ARTHROGRAPHY AS GOLD STANDARD
  DR. MARIA MURTAZA , DR MUHAMMAD AQEEL BABRI , DR. AFAF ARIF , DR. HASSAN RASHID , · TPM Testing, psychometrics,... · Dec 15, 2026

  Background: Rotator cuff tears are a common cause of shoulder pain and functional limitation. Accurate diagnosis is essential for appropriate management. While indirect MR arthrography (MRA) is considered the gold standard, plain MRI is wid…

• DIAGNOSTIC ACCURACY OF MRI IN DETECTING ROTATOR CUFF TEARS TAKING INDIRECT MR ARTHROGRAPHY AS GOLD STANDARD
  DR. MARIA MURTAZA , DR MUHAMMAD AQEEL BABRI , DR. AFAF ARIF , DR. HASSAN RASHID , · TPM Testing, psychometrics,... · Dec 15, 2026

  Background: Rotator cuff tears are a common cause of shoulder pain and functional limitation. Accurate diagnosis is essential for appropriate management. While indirect MR arthrography (MRA) is considered the gold standard, plain MRI is wid…

• Sequence-based artificial intelligence-guided inhibitory peptides to counteract AAV neutralizing antibodies in gene therapy.
  Bingqi Xu, Xin Zhang, Dandan Yu, Panjing Wang et al. · PubMed Central · Dec 10, 2026

  Adeno-associated virus (AAV) vectors have demonstrated strong clinical efficacy across multiple monogenic disorders, yet neutralizing antibodies (NAbs) remain major barriers to vector redosing and durable transduction. To address this limit…

• Internal Jugular Compression Syndrome Because of Compression Between the Styloid Process and C1 Transverse Process: Clinical Presentation, Diagnosis, and Management.
  Varadaraya Satyanarayan Shenoy, Tyler T. Lazaro, Margot Kelly-Hedrick, Landon Basner et al. · PubMed · Dec 1, 2026

  BACKGROUND AND OBJECTIVES: Internal jugular vein (IJV) compression at the skull base represents a rare cause of cerebral venous outflow obstruction and may mimic Eagle's syndrome. Unlike classic Eagle's syndrome, this condition results from…

• Towards Early and Accurate Disease Detection Through Multimodal Predictive Modeling: Fusion of Electronic Health Records, Medical Imaging, And Omics Data Using Interpretable Machine Learning.
  Muhammad Ahsan Hayat, Jahangir Baig, Shayan Ahmed, Ahmed Faraz Ayubi · Policy Research Journal · Nov 3, 2026

  Early detection of disease is a cornerstone for improving patient outcomes, reducing costs, and enabling preventative interventions. Traditional predictive models often rely on a single type of data (e.g., imaging, clinical labs, or genomic…

• Mapping of individual somatosensory representations - comparison of fMRI and TMS.
  Juha Gogulski, Mikko Nyrhinen, Rasmus Zetter, Maksym Tokariev et al. · PubMed · Nov 1, 2026
• Beyond Ground Truth: A Heuristic Unsupervised Quality Assurance Engine for Diagnosing Calibrational Blindness in Dental Segmentation
  Fatematuj Johura Mim · arXiv · Oct 29, 2026

  In real-world clinical settings, dental X-ray segmentation using deep learning methods suffers from reliability issues. Even when the segmentation quality is bad, deep learning models show high confidence in their predictions (calibrational…

• RADIOlogy: A Single-Pass Approach to Training-Free Zero-Shot Anomaly Detection
  Joaquín Figueira, Giacomo D'Amicantonio, Egor Bondarau · arXiv · Oct 29, 2026

  Current zero-shot anomaly detection methods often rely on complex prompt-learning techniques or computationally expensive sliding-window strategies to achieve fine-grained visual alignment to detect small-scale anomalies. This reliance stem…

• Accurate MRI-free PET Quantification and Reliability Assessment via CT-to-MRI Synthesis and Conformal Prediction
  Jungwoo Seo, Seung Yun Choi, Kun Ho Lee, Seun Jeon et al. · arXiv · Oct 29, 2026

  Standardized uptake value ratio (SUVR) quantification of amyloid PET commonly relies on a subject-specific T1-weighted MRI, yet a usable MRI is not always available. We therefore combined CT-to-MRI synthesis with conformal prediction for MR…

• InfantNet: A Large Scale Dataset for Infant Body Pose and Shape Estimation
  Zhipeng Hui, Jiahao Wang, Xun Dong, Guofeng Zhang et al. · arXiv · Oct 29, 2026

  Infant pose and shape estimation is essential for applications in childcare, developmental monitoring, and medical diagnosis. However, existing methods and datasets are largely designed for adults, and direct transfer to infants fails due t…

• Radiology Guideline-derived Decision Graph for Efficient Clinical Decision Support
  Xuewen Zhou, Zhen Chen · arXiv · Oct 29, 2026

  Radiological risk stratification and management planning are essential downstream tasks in medical imaging. Automating these tasks is challenging because clinical guideline criteria are distributed across prose, tables, and cross-referenced…

• Self-training for cross-centre coronary vessel segmentation in X-ray angiography using pre-contrast frame subtraction
  Danial Moafi, Aida Moafi, Mostafa Aryafar, Ashkan Sami et al. · arXiv · Oct 29, 2026

  Deep learning models for coronary vessel segmentation in X-ray angiography often perform poorly on data from centres that were not represented in training. Apart from differences in equipment, the labels of the largest public dataset (ARCAD…

• LoRe-MIM: Lost-or-Replaced Masked Image Modeling for Self-Supervised Representation Learning in Whole-Body PET/CT
  Amartya Bhattacharya, Bashirul Azam Biswas, Biratal Raj Wagle, Michael S. Leapman et al. · arXiv · Oct 29, 2026

  Deep learning models for whole-body positron emission tomography/computed tomography (PET/CT) hold significant clinical potential for disease detection, treatment planning, and response assessment. However, the time and cost associated with…

• Learning a Motion Manifold to Constrain Ambiguity in Unsupervised 4D Medical Image Interpolation
  Haojin Li, Huazhu Fu, Heng Li, Jiang Liu · arXiv · Oct 29, 2026

  Unsupervised 4D medical image interpolation reconstructs intermediate anatomical states from temporally sparse observations without intermediate supervision. Distinct motion fields may attain comparable endpoint agreement while producing di…

• SynthFaces: Balanced Large Scale Human Dataset
  Sergey Karpukhin, Denis Bobkov, Kirill Morozov, Aibek Alanov · arXiv · Oct 29, 2026

  The pursuit of fair and equitable AI in human-centric tasks is critically hindered by the inherent biases and privacy risks of real-world datasets, which offer imbalanced representations of identity and often contain sensitive personal info…

• RepConTUR: A Report-Conditioned Volumetric Multimodal Model for Abdominal Tumor Segmentation
  Seunghwan Lee, Sangjoon Park, Jongmin Lee, Yoon Jo Kim et al. · arXiv · Oct 29, 2026

  Tumor delineation is required for radiotherapy planning, yet automatic segmentation is limited by errors, predominantly false positives, that distort dose and increase editing time. The radiology report accompanies the scan and localizes di…

• Morphology-Aware Channel-Decoupled Mamba Network for Medical Image Segmentation
  Chenchen Wang, You Zhou · arXiv · Oct 29, 2026

  Accurate multi-organ segmentation in computed tomography (CT) is essential for computer-aided diagnosis, treatment planning, and disease monitoring. However, substantial variations in organ shape and size, together with low tissue contrast …

• How Reliable Is Individualized Functional-Network Attribution in Resting-State fMRI Cognitive Prediction in ADNI?
  Sheethal Bhat, Mahfuzur Rahman Chowdhury, Imam Ahmed Shaik, Rose Dawn Bharath et al. · arXiv · Oct 27, 2026

  Individualized attribution estimates which functional networks drive a model prediction for a given subject and is often proposed as an interpretable resting-state fMRI (rs-fMRI) biomarker, but its test-retest reliability is rarely quantifi…

• Segmentation Confidence for Arbitrary CNNs
  Baris Oguz, Xing Yao, Claudia Tawil, Alison Pouch et al. · arXiv · Oct 27, 2026

  Convolutional neural networks (CNN) are widely used for medical image segmentation. However, they lack an inherent measure of confidence. Existing methods for estimating prediction uncertainty often require a custom network architecture and…

• A Lightweight Attention-Based CNN with Saliency-Map Interpretability for Skin Cancer Detection
  Sanjana Islam Kasfia, Md. Ismiel Hossen Abir, AKM Bahalul Haque, Abir Mahmud Shahariar · arXiv · Oct 27, 2026

  Skin cancer is among the most prevalent and life threatening forms of cancer worldwide. Early and accurate diagnosis significantly improves patient survival rates. However, manual dermoscopic assessment remains challenging due to visual sim…

• Retrospective macromolecular pool fraction mapping from conventional clinical MRI: a physics-guided self-supervised deep learning framework
  Jelmer van Lune, Miha Fuderer, Oscar van der Heide, Matteo Maspero et al. · arXiv · Oct 27, 2026

  Macromolecular pool fraction (MPF) is a quantitative imaging biomarker sensitive to myelin integrity and other changes in tissue macromolecular content, but specialized acquisitions and reconstruction methods limit its use in large-scale st…

• MRI-to-CT Translation of Spinal Images via Anatomy-Guided Pseudo-Pairing and Adversarial Diffusion
  Eduardo Nieto, Ibai Genua, Davide Scorza, Karen López-Linares · arXiv · Oct 27, 2026

  Magnetic Resonance Imaging (MRI) is routinely used to diagnose spinal disorders, but surgical planning often requires Computed Tomography (CT) for better visualization of vertebral bone anatomy. Synthesizing CT from MRI could avoid addition…

• MCP-Net: Real-Time Coronary Perception Network and Topological Analysis for Robotic Guidewire Navigation
  Sahar Nasirihaghighi, Tianyuan Wang, Kenan Niu, Stefano Stramigioli · arXiv · Oct 27, 2026

  Coronary guidewire navigation during percutaneous coronary intervention requires continuous interpretation of vessel anatomy, guidewire position, and target stenosis under two-dimensional X-ray fluoroscopy. While existing approaches commonl…

• VPR-Space: A Benchmark for Visual Place Recognition in Space Analog Domains
  Richard Fechner, Peer Neubert · arXiv · Oct 26, 2026

  Visual Place Recognition (VPR) is an important means for loop closure detection in visual Simultaneous Localization and Mapping (SLAM). While state-of-the-art VPR and SLAM approaches excel in urban and feature-rich natural environments, the…

• Toward Clinical Translation of Deep Learning-Based Intracranial Super-Resolution 4D Flow MRI Using Multi-Cohort Transfer Learning
  Oliver Welin Odeback, Susanne Schnell, Patrick Winter, Johan Lundberg et al. · arXiv · Oct 26, 2026

  We evaluated synthetic pretraining and multi-cohort transfer learning for deep learning-based super-resolution of intracranial 4D Flow MRI across heterogeneous neurologic cohorts. This mixed prospective-retrospective study analyzed 18 parti…

• VTRL-Med: Progressive Visual Refinement with Topology-Guided Regularization for Medical Image Clustering
  Guangyu Meng, Pengfei Gu, Peixian Liang, John P. Lalor et al. · arXiv · Oct 23, 2026

  Deep clustering offers a promising approach for analyzing large unlabeled medical image datasets, yet prevailing methods still face two limitations: they may neglect class-agnostic structural priors that capture object boundaries and region…