1.3k citations · 7.9k across the 178 of their papers we have counts for
23 papers · 1 filter
See More, Change Less: Anatomy-Aware Diffusion for Contrast Enhancement
Junqi Liu, Zejun Wu, Pedro R. A. S. Bassi +15
Image enhancement improves visual quality and helps reveal details that are hard to see in the original image. In medical imaging, it can support clinical decision-making, but curr…
The MICCAI Federated Tumor Segmentation (FeTS) Challenge 2024: Efficient and Robust Aggregation Methods for Federated Learning
Akis Linardos, Sarthak Pati, Ujjwal Baid +25
We present the design and results of the MICCAI Federated Tumor Segmentation (FeTS) Challenge 2024, which focuses on federated learning (FL) for glioma sub-region segmentation in m…
In search of truth: Evaluating concordance of AI-based anatomy segmentation models
Lena Giebeler, Deepa Krishnaswamy, David Clunie +9
Purpose AI-based methods for anatomy segmentation can help automate characterization of large imaging datasets. The growing number of similar in functionality models raises the cha…
Hide-and-Seek Attribution: Weakly Supervised Segmentation of Vertebral Metastases in CT
Matan Atad, Alexander W. Marka, Lisa Steinhelfer +10
Accurate segmentation of vertebral metastasis in CT is clinically important yet difficult to scale, as voxel-level annotations are scarce and both lytic and blastic lesions often r…
Better Tokens for Better 3D: Advancing Vision-Language Modeling in 3D Medical Imaging
Ibrahim Ethem Hamamci, Sezgin Er, Suprosanna Shit +7
Recent progress in vision-language modeling for 3D medical imaging has been fueled by large-scale computed tomography (CT) corpora with paired free-text reports, stronger architect…
RadDiagSeg-M: A Vision Language Model for Joint Diagnosis and Multi-Target Segmentation in Radiology
Chengrun Li, Corentin Royer, Haozhe Luo +6
Most current medical vision language models struggle to jointly generate diagnostic text and pixel-level segmentation masks in response to complex visual questions. This represents…
Scaling Artificial Intelligence for Multi-Tumor Early Detection with More Reports, Fewer Masks
Pedro R. A. S. Bassi, Xinze Zhou, Wenxuan Li +20
Early tumor detection save lives. Each year, more than 300 million computed tomography (CT) scans are performed worldwide, offering a vast opportunity for effective cancer screenin…
Circle of Willis Centerline Graphs: A Dataset and Baseline Algorithm
Fabio Musio, Norman Juchler, Kaiyuan Yang +4
The Circle of Willis (CoW) is a critical network of arteries in the brain, often implicated in cerebrovascular pathologies. Voxel-level segmentation is an important first step towa…
MInDI-3D: Iterative Deep Learning in 3D for Sparse-view Cone Beam Computed Tomography
Daniel Barco, Marc Stadelmann, Martin Oswald +7
We present MInDI-3D (Medical Inversion by Direct Iteration in 3D), the first 3D conditional diffusion-based model for real-world sparse-view Cone Beam Computed Tomography (CBCT) ar…
CADS: A Comprehensive Anatomical Dataset and Segmentation for Whole-Body Anatomy in Computed Tomography
Murong Xu, Tamaz Amiranashvili, Fernando Navarro +30
Accurate delineation of anatomical structures in volumetric CT scans is crucial for diagnosis and treatment planning. While AI has advanced automated segmentation, current approach…
fastWDM3D: Fast and Accurate 3D Healthy Tissue Inpainting
Alicia Durrer, Florentin Bieder, Paul Friedrich +3
Healthy tissue inpainting has significant applications, including the generation of pseudo-healthy baselines for tumor growth models and the facilitation of image registration. In…
BrainLesion Suite: A Flexible and User-Friendly Framework for Modular Brain Lesion Image Analysis
Florian Kofler, Marcel Rosier, Mehdi Astaraki +26
BrainLesion Suite is a versatile toolkit for building modular brain lesion image analysis pipelines in Python. Following Pythonic principles, BrainLesion Suite is designed to provi…
Semantically Consistent Discrete Diffusion for 3D Biological Graph Modeling
Chinmay Prabhakar, Suprosanna Shit, Tamaz Amiranashvili +2
3D spatial graphs play a crucial role in biological and clinical research by modeling anatomical networks such as blood vessels,neurons, and airways. However, generating 3D biologi…
Parametric shape models for vessels learned from segmentations via differentiable voxelization
Alina F. Dima, Suprosanna Shit, Huaqi Qiu +8
Vessels are complex structures in the body that have been studied extensively in multiple representations. While voxelization is the most common of them, meshes and parametric mode…
Physics informed guided diffusion for accelerated multi-parametric MRI reconstruction
Perla Mayo, Carolin M. Pirkl, Alin Achim +2
We introduce MRF-DiPh, a novel physics informed denoising diffusion approach for multiparametric tissue mapping from highly accelerated, transient-state quantitative MRI acquisitio…
BraTS orchestrator : Democratizing and Disseminating state-of-the-art brain tumor image analysis
Florian Kofler, Marcel Rosier, Mehdi Astaraki +34
The Brain Tumor Segmentation (BraTS) cluster of challenges has significantly advanced brain tumor image analysis by providing large, curated datasets and addressing clinically rele…
CRG Score: A Distribution-Aware Clinical Metric for Radiology Report Generation
Ibrahim Ethem Hamamci, Sezgin Er, Suprosanna Shit +3
Evaluating long-context radiology report generation is challenging. NLG metrics fail to capture clinical correctness, while LLM-based metrics often lack generalizability. Clinical…
Automated Thoracolumbar Stump Rib Detection and Analysis in a Large CT Cohort
Hendrik Möller, Hanna Schön, Alina Dima +10
Thoracolumbar stump ribs are one of the essential indicators of thoracolumbar transitional vertebrae or enumeration anomalies. While some studies manually assess these anomalies an…
Analysis of the MICCAI Brain Tumor Segmentation -- Metastases (BraTS-METS) 2025 Lighthouse Challenge: Brain Metastasis Segmentation on Pre- and Post-treatment MRI
Nazanin Maleki, Raisa Amiruddin, Ahmed W. Moawad +240
Despite continuous advancements in cancer treatment, brain metastatic disease remains a significant complication of primary cancer and is associated with an unfavorable prognosis.…
Energy Matching: Unifying Flow Matching and Energy-Based Models for Generative Modeling
Michal Balcerak, Tamaz Amiranashvili, Antonio Terpin +5
Current state-of-the-art generative models map noise to data distributions by matching flows or scores. A key limitation of these models is their inability to readily integrate ava…
Towards contrast- and pathology-agnostic clinical fetal brain MRI segmentation using SynthSeg
Ziyao Shang, Misha Kaandorp, Kelly Payette +9
Magnetic resonance imaging (MRI) has played a crucial role in fetal neurodevelopmental research. Structural annotations of MR images are an important step for quantitative analysis…
PARASIDE: An Automatic Paranasal Sinus Segmentation and Structure Analysis Tool for MRI
Hendrik Möller, Lukas Krautschick, Matan Atad +9
Chronic rhinosinusitis (CRS) is a common and persistent sinus imflammation that affects 5 - 12\% of the general population. It significantly impacts quality of life and is often di…
Efficient Deep Learning-based Forward Solvers for Brain Tumor Growth Models
Zeineb Haouari, Jonas Weidner, Yeray Martin-Ruisanchez +5
Glioblastoma, a highly aggressive brain tumor, poses major challenges due to its poor prognosis and high morbidity rates. Partial differential equation-based models offer promising…