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VERIDAH: Solving Enumeration Anomaly Aware Vertebra Labeling across Imaging Sequences
Hendrik Möller, Hanna Schoen, Robert Graf +14
The human spine commonly consists of seven cervical, twelve thoracic, and five lumbar vertebrae. However, enumeration anomalies may result in individuals having eleven or thirteen…
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…
DeViDe: Faceted medical knowledge for improved medical vision-language pre-training
Haozhe Luo, Ziyu Zhou, Corentin Royer +2
Vision-language pre-training for chest X-rays has made significant strides, primarily by utilizing paired radiographs and radiology reports. However, existing approaches often face…
Enhancing Interpretability of Vertebrae Fracture Grading using Human-interpretable Prototypes
Poulami Sinhamahapatra, Suprosanna Shit, Anjany Sekuboyina +7
Vertebral fracture grading classifies the severity of vertebral fractures, which is a challenging task in medical imaging and has recently attracted Deep Learning (DL) models. Only…
Generalist Foundation Models from a Multimodal Dataset for 3D Computed Tomography
Ibrahim Ethem Hamamci, Sezgin Er, Chenyu Wang +27
Advancements in medical imaging AI, particularly in 3D imaging, have been limited due to the scarcity of comprehensive datasets. We introduce CT-RATE, a public dataset that pairs 3…
MultiMedEval: A Benchmark and a Toolkit for Evaluating Medical Vision-Language Models
Corentin Royer, Bjoern Menze, Anjany Sekuboyina
We introduce MultiMedEval, an open-source toolkit for fair and reproducible evaluation of large, medical vision-language models (VLM). MultiMedEval comprehensively assesses the mod…
The TopCoW Challenge -- Topology-Aware Circle of Willis Segmentation for CT and MR Angiography
Kaiyuan Yang, Fabio Musio, Yihui Ma +112
The Circle of Willis (CoW) is an important network of arteries connecting major circulations of the brain. Its vascular architecture is believed to influence the risk, severity, an…
MedShapeNet -- A Large-Scale Dataset of 3D Medical Shapes for Computer Vision
Jianning Li, Zongwei Zhou, Jiancheng Yang +154
Prior to the deep learning era, shape was commonly used to describe the objects. Nowadays, state-of-the-art (SOTA) algorithms in medical imaging are predominantly diverging from co…
GenerateCT: Text-Conditional Generation of 3D Chest CT Volumes
Ibrahim Ethem Hamamci, Sezgin Er, Anjany Sekuboyina +13
GenerateCT, the first approach to generating 3D medical imaging conditioned on free-form medical text prompts, incorporates a text encoder and three key components: a novel causal…
Diffusion-Based Hierarchical Multi-Label Object Detection to Analyze Panoramic Dental X-rays
Ibrahim Ethem Hamamci, Sezgin Er, Enis Simsar +5
Due to the necessity for precise treatment planning, the use of panoramic X-rays to identify different dental diseases has tremendously increased. Although numerous ML models have…
Evaluating the Robustness of Self-Supervised Learning in Medical Imaging
Fernando Navarro, Christopher Watanabe, Suprosanna Shit +4
Self-supervision has demonstrated to be an effective learning strategy when training target tasks on small annotated data-sets. While current research focuses on creating novel pre…
The MICCAI Hackathon on reproducibility, diversity, and selection of papers at the MICCAI conference
Fabian Balsiger, Alain Jungo, Naren Akash R J +12
The MICCAI conference has encountered tremendous growth over the last years in terms of the size of the community, as well as the number of contributions and their technical succes…
clDice -- A Novel Topology-Preserving Loss Function for Tubular Structure Segmentation
Suprosanna Shit, Johannes C. Paetzold, Anjany Sekuboyina +6
Accurate segmentation of tubular, network-like structures, such as vessels, neurons, or roads, is relevant to many fields of research. For such structures, the topology is their mo…
VerSe: A Vertebrae Labelling and Segmentation Benchmark for Multi-detector CT Images
Anjany Sekuboyina, Malek E. Husseini, Amirhossein Bayat +66
Vertebral labelling and segmentation are two fundamental tasks in an automated spine processing pipeline. Reliable and accurate processing of spine images is expected to benefit cl…
DiamondGAN: Unified Multi-Modal Generative Adversarial Networks for MRI Sequences Synthesis
Hongwei Li, Johannes C. Paetzold, Anjany Sekuboyina +5
Synthesizing MR imaging sequences is highly relevant in clinical practice, as single sequences are often missing or are of poor quality (e.g. due to motion). Naturally, the idea ar…
Labelling Vertebrae with 2D Reformations of Multidetector CT Images: An Adversarial Approach for Incorporating Prior Knowledge of Spine Anatomy
Anjany Sekuboyina, Markus Rempfler, Alexander Valentinitsch +2
Purpose: To use and test a labelling algorithm that operates on two-dimensional (2D) reformations, rather than three-dimensional (3D) data to locate and identify vertebrae. Methods…
The Liver Tumor Segmentation Benchmark (LiTS)
Patrick Bilic, Patrick Christ, Hongwei Bran Li +106
In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LiTS), which was organized in conjunction with the IEEE International Symposium on Biomedi…
Multi-level Activation for Segmentation of Hierarchically-nested Classes
Marie Piraud, Anjany Sekuboyina, Bjoern H. Menze
For many biological image segmentation tasks, including topological knowledge, such as the nesting of classes, can greatly improve results. However, most `out-of-the-box' CNN model…
Btrfly Net: Vertebrae Labelling with Energy-based Adversarial Learning of Local Spine Prior
Anjany Sekuboyina, Markus Rempfler, Jan Kukačka +4
Robust localisation and identification of vertebrae is essential for automated spine analysis. The contribution of this work to the task is two-fold: (1) Inspired by the human expe…
A Localisation-Segmentation Approach for Multi-label Annotation of Lumbar Vertebrae using Deep Nets
Anjany Sekuboyina, Alexander Valentinitsch, Jan S. Kirschke +1
Multi-class segmentation of vertebrae is a non-trivial task mainly due to the high correlation in the appearance of adjacent vertebrae. Hence, such a task calls for the considerati…