In this study, we introduce a deep learning approach for segmenting kidn...
Accurate identification of emphysema subtypes and severity is crucial fo...
This paper presents a large publicly available multi-center lumbar spine...
Challenges drive the state-of-the-art of automated medical image analysi...
Recently, large, high-quality public datasets have led to the developmen...
We present a novel graph-based approach for labeling the anatomical bran...
To date few studies have comprehensively compared medical image registra...
Semantic segmentation neural networks require pixel-level annotations in...
We propose a deep learning clustering method that exploits dense feature...
Automatic lesion segmentation on thoracic CT enables rapid quantitative
...
Total lung volume is an important quantitative biomarker and is used for...
While the importance of automatic image analysis is increasing at an eno...
In the context of the current global pandemic and the limitations of the...
Recent advances in deep learning have led to a promising performance in ...
We propose a novel framework for controllable pathological image synthes...
Deep-learning-based registration methods emerged as a fast alternative t...
Background and Objective: Accurate and reliable segmentation of the pros...
Amidst the ongoing pandemic, several studies have shown that COVID-19
cl...
Pulmonary lobe segmentation in computed tomography scans is essential fo...
Random transformations are commonly used for augmentation of the trainin...
Due to memory constraints on current hardware, most convolution neural
n...
Interpretability of deep learning (DL) systems is gaining attention in
m...
The number of biomedical image analysis challenges organized per year is...
Chronic Obstructive Pulmonary Disease (COPD) is a leading cause of morbi...
Chronic Obstructive Pulmonary Disease (COPD) is a leading cause of morbi...
We present a novel multilevel approach for deep learning based image
reg...
Purpose: To develop and validate a deep learning model for automatic
seg...
The Gleason score is the most important prognostic marker for prostate c...
In this work, we propose a method to reject out-of-distribution samples ...
Purpose: To validate the performance of a commercially-available,
CE-cer...
There is a growing interest in the automated analysis of chest X-Ray (CX...
Semantic segmentation of medical images aims to associate a pixel with a...
In this work, we report the set-up and results of the Liver Tumor
Segmen...
Chest X-rays are one of the most commonly used technologies for medical
...
We propose iW-Net, a deep learning model that allows for both automatic ...
Generative Adversarial Networks (GANs) and their extensions have carved ...
Generative adversarial networks have been successfully applied to inpain...
Prostate cancer (PCa) is graded by pathologists by examining the
archite...
International challenges have become the standard for validation of
biom...
Precise segmentation of the vertebrae is often required for automatic
de...
Ventricular volume and its progression are known to be linked to several...
Heavy smokers undergoing screening with low-dose chest CT are affected b...
Automated classification of histopathological whole-slide images (WSI) o...
Tissue segmentation is an important pre-requisite for efficient and accu...
Magnetic Resonance Imaging (MRI) is widely used in routine clinical diag...
Automatic detection of pulmonary nodules in thoracic computed tomography...
The introduction of lung cancer screening programs will produce an
unpre...
Lacunes of presumed vascular origin (lacunes) are associated with an
inc...
The anatomical location of imaging features is of crucial importance for...