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Memory-based unsupervised video clinical quality assessment with multi-modality data in fetal ultrasound
Memory-based unsupervised video clinical quality assessment with multi-modality data in fetal ultrasound
In obstetric sonography, the quality of acquisition of ultrasound scan video is crucial for accurate (manual or automated)...
Spatio-temporal physics-informed learning: A novel approach to CT perfusion analysis in acute ischemic stroke
Spatio-temporal physics-informed learning: A novel approach to CT perfusion analysis in acute ischemic stroke
CT perfusion imaging is important in the imaging workup of acute ischemic stroke for evaluating affected cerebral tissue. ...
Latent Transformer Models for out-of-distribution detection
Latent Transformer Models for out-of-distribution detection
Any clinically-deployed image-processing pipeline must be robust to the full range of inputs it may be presented with. One...
Bone mineral density estimation from a plain X-ray image by learning decomposition into projections of bone-segmented computed tomography
Bone mineral density estimation from a plain X-ray image by learning decomposition into projections of bone-segmented computed tomography
In the last decades, a significant increase in the prevalence of osteoporosis has been observed. It has become the most co...
Learning joint surface reconstruction and segmentation, from brain images to cortical surface parcellation
Learning joint surface reconstruction and segmentation, from brain images to cortical surface parcellation
Brain surface analysis requires the accurate reconstruction and segmentation of cortical surfaces from MRI volumes (Querbe...
Dynamic feature splicing for few-shot rare disease diagnosis
Dynamic feature splicing for few-shot rare disease diagnosis
Deep learning models have achieved impressive breakthroughs on many medical image analysis tasks, e.g., anatomical structu...
A deep weakly semi-supervised framework for endoscopic lesion segmentation
A deep weakly semi-supervised framework for endoscopic lesion segmentation
As a diagnostic examination manner, the endoscopy imaging has been widely adopted in medical field for the screening of va...
Joint localization and classification of breast masses on ultrasound images using an auxiliary attention-based framework
Joint localization and classification of breast masses on ultrasound images using an auxiliary attention-based framework
Breast neoplasm is a commonly seen disease among women between 35–55 years of age (Pyakurel et al., 2014, Nothacker et al....
Active learning for medical image segmentation with stochastic batches
Active learning for medical image segmentation with stochastic batches
Data annotation is fundamental to medical imaging. Notably, the performance of segmentation algorithms depends on the amou...
The role of noise in denoising models for anomaly detection in medical images
The role of noise in denoising models for anomaly detection in medical images
Anomaly detection is a fundamental task in medical image analysis, mimicking the initial review that a radiologist perform...
A robust and interpretable deep learning framework for multi-modal registration via keypoints
A robust and interpretable deep learning framework for multi-modal registration via keypoints
Registration is a fundamental problem in biomedical imaging tasks. Multiple images, often reflecting a variety of contrast...
Supervised tractogram filtering using Geometric Deep Learning
Supervised tractogram filtering using Geometric Deep Learning
The purpose of this work is to leverage the brain anatomical knowledge to design a method for tractogram filtering based o...
Automatic Head and Neck Tumor segmentation and outcome prediction relying on FDG-PET/CT images: Findings from the second edition of the HECKTOR challenge
Automatic Head and Neck Tumor segmentation and outcome prediction relying on FDG-PET/CT images: Findings from the second edition of the HECKTOR challenge
By focusing on metabolic and morphological tissue properties respectively, FluoroDeoxyGlucose (FDG)-Positron Emission Tomo...
A clinically applicable AI system for diagnosis of congenital heart diseases based on computed tomography images
A clinically applicable AI system for diagnosis of congenital heart diseases based on computed tomography images
Congenital heart disease (CHD) is a type of disease caused by abnormal heart structure, which is the most common type of b...
UNesT: Local spatial representation learning with hierarchical transformer for efficient medical segmentation
UNesT: Local spatial representation learning with hierarchical transformer for efficient medical segmentation
Medical image segmentation tasks have become increasingly challenging due to the need for modeling hundreds of tissues (Hu...
One-shot segmentation of novel white matter tracts via extensive data augmentation and adaptive knowledge transfer
One-shot segmentation of novel white matter tracts via extensive data augmentation and adaptive knowledge transfer
Diffusion magnetic resonance imaging (dMRI) allows noninvasive reconstruction of white matter (WM) pathways (Jeurissen et ...
Prototypical few-shot segmentation for cross-institution male pelvic structures with spatial registration
Prototypical few-shot segmentation for cross-institution male pelvic structures with spatial registration
The prowess that makes few-shot learning desirable in medical image analysis is the efficient use of the support image dat...
Multi-site, Multi-domain Airway Tree Modeling
Multi-site, Multi-domain Airway Tree Modeling
Deep learning methods are reshaping the general practice of image segmentation. In addition to novel network designs, the ...
Ambiguity-aware breast tumor cellularity estimation via self-ensemble label distribution learning
Ambiguity-aware breast tumor cellularity estimation via self-ensemble label distribution learning
Automatic and accurate estimation of breast tumor cellularity (TC, Fig. 1) is significant for the diagnosis and prognosis ...
Colonoscopy 3D video dataset with paired depth from 2D-3D registration
Colonoscopy 3D video dataset with paired depth from 2D-3D registration
Colorectal cancer (CRC) is the second most lethal form of cancer in the United States (Siegel et al., 2021). At least 80% ...
The value of Augmented Reality in surgery — A usability study on laparoscopic liver surgery
The value of Augmented Reality in surgery — A usability study on laparoscopic liver surgery
Augmented Reality (AR) is considered to be a promising technology for the guidance of laparoscopic liver surgery. By overl...
A generic fundus image enhancement network boosted by frequency self-supervised representation learning
A generic fundus image enhancement network boosted by frequency self-supervised representation learning
Owing to the superiority in safety and cost, fundus photography has been used as a routine clinical examination to diagnos...
DefCor-Net: Physics-aware ultrasound deformation correction
DefCor-Net: Physics-aware ultrasound deformation correction
The recovery of accurate anatomical images from distorted ones is a fundamental problem in medical imaging, which contribu...
Nested star-shaped objects segmentation using diameter annotations
Nested star-shaped objects segmentation using diameter annotations
Most current deep learning based approaches for image segmentation require annotations of large datasets, which limits the...
Deep learning with explainability for characterizing age-related intrinsic differences in dynamic brain functional connectivity
Deep learning with explainability for characterizing age-related intrinsic differences in dynamic brain functional connectivity
Resting-state functional magnetic resonance imaging (rs-fMRI) is a powerful neuroimaging tool to understand the brain’s la...
Multi-cell type and multi-level graph aggregation network for cancer grading in pathology images
Multi-cell type and multi-level graph aggregation network for cancer grading in pathology images
In pathology, cancer grading is crucial for patient management and treatment. Recent deep learning methods, based upon con...
Gaussian Process-based prediction of memory performance and biomarker status in ageing and Alzheimer’s disease—A systematic model evaluation
Gaussian Process-based prediction of memory performance and biomarker status in ageing and Alzheimer’s disease—A systematic model evaluation
Neuroimaging markers based on Magnetic Resonance Imaging (MRI) combined with various other measures (such as genetic covar...
YoloCurvSeg: You only label one noisy skeleton for vessel-style curvilinear structure segmentation
YoloCurvSeg: You only label one noisy skeleton for vessel-style curvilinear structure segmentation
Curvilinear structures are elongated, curved, multi-scale structures that often appear tree-like and are commonly found in...
USE-Evaluator: Performance metrics for medical image segmentation models supervised by uncertain, small or empty reference annotations in neuroimaging
USE-Evaluator: Performance metrics for medical image segmentation models supervised by uncertain, small or empty reference annotations in neuroimaging
The performance of machine learning algorithms is assessed by metrics. The optimal choice of metrics depends on the data s...
Multi-level and joint attention networks on brain functional connectivity for cross-cognitive prediction
Multi-level and joint attention networks on brain functional connectivity for cross-cognitive prediction
In the past decade, resting-state functional magnetic resonance imaging (rs-fMRI) has been widely used to understand brain...
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