Radiology

Towards contrast- and pathology-agnostic clinical fetal brain MRI segmentation using SynthSeg.

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 of the developing human brain, with Deep Learning providing an automated alternative for this otherwise tedious manual process. However, segmentation performances of Convolutional Neural Networks often suffer from domai...

Quality of Head and Neck Diffusion-weighted MR Imaging Using a Combination of the Periodically Rotated Overlapping Parallel Lines with Enhanced Reconstruction (PROPELLER) Sequence and Deep Learning Reconstruction.

PURPOSE: To evaluate whether periodically rotated overlapping parallel lines with enhanced reconstruction-diffusion-weighted imaging (PROPELLER-DWI) combined with deep learning-based reconstruction (DLR) improves head and neck DWI, we conducted a primary comparison of PROPELLER-DWI with DLR at varying strengths and without DLR, and a secondary comparison of DLR-processed PROPELLER-DWI with DLR-pro...

Alzheimer's disease prediction via an explainable CNN using genetic algorithm and SHAP values.

Convolutional neural networks (CNNs) are widely recognized for their high precision in image classification. Nevertheless, the lack of transparency in...

Biometric Data in Post-Traumatic Stress Disorder Detection: A Scoping Review of Digital Health Applications.

CONTEXT: Post-traumatic stress disorder (PTSD) is mainly assessed through self-reports and clinician interviews, which can delay recognition and limit...

BraTioUS: A multicenter dataset of baseline intraoperative brain tumor ultrasound images.

The BraTioUS (Brain Tumor Intraoperative Ultrasound) dataset [1] is a large-scale, multicenter, and publicly available collection of intraoperative ul...

Quasi-multimodal-based pathophysiological feature learning for retinal disease diagnosis.

Retinal diseases spanning a broad spectrum can be effectively identified and diagnosed using complementary signals from multimodal data. However, mult...

Accelerated brain aging in amyotrophic lateral sclerosis and its prognostic associations: a cohort study.

BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease, appearing to be associated with accelerated brain aging. Althoug...

Correlation of Automated in Vivo Image Quality With Radiologist's Performance in Abdomen Computed Tomography Across Conventional and Deep Learning Reconstructions.

OBJECTIVE: Image quality evaluation in radiology is most relevant when reflects radiologists' performance. This study assessed how image quality measu...

Artificial Intelligence in Pleural Diseases: Current Applications and Next Steps.

Pleural diseases pose a significant burden on healthcare systems due to diagnostic challenges and high costs. Artificial intelligence (AI) has the pot...

Imaging and Quantification of Perivascular Adipose Tissue.

Perivascular adipose tissue (PVAT) is a metabolically active tissue that influences vascular function through paracrine signaling of adipokines. Patho...

Future Prospects for Using Clinical Phenotypes in Tuberculosis Precision Medicine-An Approach for Clinical Management.

Developing shorter treatment regimens for tuberculosis requires careful characterization of the clinical phenotype, which is defined by patient charac...

Stratifying amyloid burden in early Alzheimer's disease using cascaded attention-guided vision transformer using [¹⁸F]Florbetapir PET.

OBJECTIVES: This study aims to develop a deep learning model to assist physicians in accurately classifying negative, equivocal, and positive β-amyloi...

Biologically explicable multimodal model predicting local tumor progression and tumor invasiveness of hepatocellular carcinoma.

PURPOSE: Local tumor progression (LTP) of hepatocellular carcinoma (HCC) after thermal ablation (TA) is related to tumor invasiveness and threaten the...

PIPN: Physics-inspired phase retrieval network for propagation-based X-ray phase-contrast imaging.

Propagation-based X-ray phase-contrast imaging (PB-XPCI) can produce high-resolution images of soft tissue. However, this usually requires extracting ...

Prompting and Fine-Tuning Large Language Models for Parkinson Disease Diagnosis: Comparative Evaluation Study Using the PPMI Structured Dataset.

BACKGROUND: Parkinson disease (PD) presents diagnostic challenges due to its heterogeneous motor and nonmotor manifestations. Traditional machine lear...

BreastDCEDL: A standardized deep learning-ready breast DCE-MRI dataset of 2,070 patients.

Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) is essential for monitoring breast cancer treatment response, yet deep learning progres...

Reducing bulky medical images via shape-texture decoupled deep neural networks.

The explosive growth of medical data poses significant challenges for storage and sharing. Current compression techniques utilizing Implicit Neural Re...

Active guidance in ultrasound bladder scanning using reinforcement learning.

Accurate measurement of bladder volume is essential for diagnosing urinary retention and voiding dysfunction. However, finding optimal view can be cha...

Prospective study assessing the validity of accelerated 2D Fast Spin Echo (2D FSE) based high-resolution knee MRI and T2 mapping using deep learning reconstruction.

BACKGROUND: A routine fast spin-echo (FSE) MRI protocol is widely used to evaluate structural injuries of the knee. While adding a T2 mapping sequence...

The balance between artificial and human intelligence in clinical practice.

INTRODUCTION: Artificial intelligence (AI) is becoming increasingly integrated into clinical care in hand surgery. Its applications extend across diag...