Radiology

A probabilistic deep learning approach for choroid plexus segmentation in autism spectrum disorder.

The choroid plexus serves as the primary barrier between the brain's blood and cerebrospinal fluid and mediates neuroimmune function. A subset of individuals with autism spectrum disorder (ASD) may exhibit morphological alterations of the choroid plexus. However, to power larger population analyses, an automated tool capable of accurately segmenting the choroid plexus based on magnetic resonance i...

Multimodal deep learning for laryngeal squamous cell carcinoma staging using CT and laryngoscopy.

OBJECTIVES: To develop and validate a multimodal deep learning model integrating clinical data, contrast-enhanced CT, and laryngoscopic images for differentiating early-stage (I-II) from advanced-stage (III-IV) laryngeal squamous cell carcinoma (LSCC). MATERIALS AND METHODS: This retrospective multicenter study included 450 patients with pathologically confirmed LSCC from two Chinese medical cente...

deepmriprep: voxel-based morphometry preprocessing via deep neural networks.

Voxel-based morphometry (VBM), a popular approach in neuroimaging research, uses magnetic resonance imaging data to assess variations in the local den...

A clinically applicable and generalizable deep learning model for anterior mediastinal tumors in CT images across multiple institutions.

Rare diseases are often difficult to diagnose, and their scarcity also makes it challenging to develop deep learning models for them due to limited la...

A dual-task deep learning framework for automated detection and classification of coronary artery lesions in invasive coronary angiography imaging.

OBJECTIVE: This study aims to develop and evaluate a dual-task deep learning framework for the simultaneous detection and classification of coronary l...

RNA2seg: a generalist model for cell segmentation in image-based spatial transcriptomics.

Imaging-based spatial transcriptomics enables high-resolution spatial mapping of RNA species. A key challenge in imaging-based spatial transcriptomics...

Group equivariant pyramid network for respiratory motion correction on PET image.

INTRODUCTION: Respiratory-induced artefacts cause blurring in PET images, impairing lesion identification and diagnosis. Existing correction methods e...

Technical accuracy of AI-based patient autopositioning in Computed Tomography: An evaluation with dose monitoring system data.

INTRODUCTION: Recent advancements in Artificial Intelligence (AI)-driven algorithms have improved patient alignment in Computed Tomography (CT) imagin...

Predicting transcranial ultrasound insertion loss using skull CT: A deep learning approach.

Transcranial ultrasound (tUS) is a non-invasive neuromodulation technique with applications in brain disorders. However, ultrasound attenuation induce...

Feasibility of single-phase DECT as an alternative to triple-phase CT for imaging-defined risk factors assessment in neuroblastoma for dose reduction.

OBJECTIVE: To investigate the feasibility of evaluating Imaging-Defined Risk Factors (IDRFs) in Neuroblastoma (NB) patients using venous-phase (VP)-on...

Asymmetric fiber orientation distribution estimation via unsupervised deep learning.

Diffusion magnetic resonance imaging (dMRI) tractography is a key technique for reconstructing brain structural connectivity. A widely recognized limi...

From prostate-specific antigen to precision: The future of prostate cancer diagnosis with artificial intelligence, biomarkers, and imaging.

BACKGROUND: Prostate cancer (PCa) diagnosis has historically relied on prostate-specific antigen (PSA) testing. Although PSA screening significantly r...

Real-Time and Precise 3-D Lesion Reconstruction With Boundary Point Clouds for Robotic Ultrasound Scanning.

In robot-assisted breast ultrasound scanning, conventional 2-D imaging often fails to fully capture the spatial morphology of lesions, limiting clinic...

Application of machine learning for sex-specific risk prediction of coronary artery calcification.

BACKGROUND AND AIMS: Sex-related differences in coronary artery calcium (CAC) burden and risk are well known but often ignored in traditional models. ...

Image quality comparison between low-dose thin-slice deep-learning reconstruction and standard-dose thick-slice hybrid iterative reconstruction in pediatric abdominal CT.

OBJECTIVES: To compare image quality between low-dose thin-slice deep-learning reconstruction (DLR) and standard-dose thick-slice hybrid iterative rec...

Liquid biopsy biomarkers for accurate detection of malignant pulmonary nodules: a meta-analytic approach.

UNLABELLED: Pulmonary nodules are a common radiological finding that can be classified as either benign or Malignant, with significant clinical implic...

Ultrasound-Based Kidney Stone Classification Using Kronecker Self-Organizing Map Forward Harmonic Network.

Kidney stone disease is a prevalent urological disorder that can result in severe pain, obstruction, and long-term complications if not detected and m...

From inhibition to regulation: serpins in health and disease.

This issue of the Biomedical Journal highlights regulatory mechanisms that shape aging, disease progression, and biological complexity across molecula...

Anti-Inflammatory Properties of Dendrobium: A Systematic Review of Pharmacological Mechanisms.

ETHNOPHARMACOLOGICAL RELEVANCE: In Traditional Chinese Medicine (TCM), Dendrobium species have long been utilized to alleviate various inflammatory sy...

Deep Learning Model with Nodule Indexing Tailored to Early-Stage Lung Cancer Detection.

OBJECTIVE: To evaluate whether a deep learning-based AI system with suspected nodule indexing and malignancy risk stratification improves radiologist ...