AIMC Topic: Gallbladder

Clear Filters Showing 1 to 10 of 15 articles

Evaluating Multiple Input Strategies of Large Language Models for Gallbladder Polyps on Ultrasound: Comparative Study.

JMIR medical informatics
BACKGROUND: Gallbladder polyps have a high prevalence and are predominantly benign lesions, often detected via ultrasound. They impose diagnostic burdens on radiologists while generating substantial patient demand for report interpretation. Benign po...

Enhanced gallbladder cancer detection via active and self-supervised learning integration: Innovating B-ultrasound image analysis.

PloS one
Gallbladder cancer, a common yet often under diagnosed malignancy, is typically characterized by late detection and a poor prognosis. The rise of deep learning has introduced new methods for its early identification through B-ultrasound imaging, but ...

Multi-spatial-attention U-Net: a novel framework for automated gallbladder segmentation on CT images.

BMC medical imaging
OBJECTIVE: This study aimed to construct a novel model, Multi-Spatial Attention U-Net (MSAU-Net) by incorporating our proposed Multi-Spatial Attention (MSA) block into the U-Net for the automated segmentation of the gallbladder on CT images.

GBCHV an advanced deep learning anatomy aware model for accurate classification of gallbladder cancer utilizing ultrasound images.

Scientific reports
This study introduces a novel deep learning approach aimed at accurately classifying Gallbladder Cancer (GBC) into benign, malignant, and normal categories using ultrasound images from the challenging GBC USG (GBCU) dataset. The proposed methodology ...

Machine learning-based prognostic modeling in gallbladder cancer using clinical data and pre-treatment [F]-FDG-PET-radiomic features.

Japanese journal of radiology
OBJECTIVES: This study evaluates the effectiveness of machine learning (ML) models that incorporate clinical and 2-deoxy-2-[F]fluoro-D-glucose ([F]-FDG)-positron emission tomography (PET)-radiomic features for predicting outcomes in gallbladder cance...

Exploring Deep Learning Applications using Ultrasound Single View Cines in Acute Gallbladder Pathologies: Preliminary Results.

Academic radiology
RATIONALE AND OBJECTIVES: In this preliminary study, we aimed to develop a deep learning model using ultrasound single view cines that distinguishes between imaging of normal gallbladder, non-urgent cholelithiasis, and acute calculous cholecystitis r...

The value of CT radiomics combined with deep transfer learning in predicting the nature of gallbladder polypoid lesions.

Acta radiologica (Stockholm, Sweden : 1987)
BACKGROUND: Computed tomography (CT) radiomics combined with deep transfer learning was used to identify cholesterol and adenomatous gallbladder polyps that have not been well evaluated before surgery.

Multiple instance convolutional neural network for gallbladder assessment from laparoscopic images.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: We present an artificial intelligence framework for vascularity classification of the gallbladder (GB) wall from intraoperative images of laparoscopic cholecystectomy (LC).

Does single-site robotic surgery makes sense for gallbladder surgery?

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Cholecystectomy is one of the most performed surgeries. Several techniques were created, generating less pain, better aesthetic results and faster return to activities. Robotic surgery through a single portal combined the advantages of si...

Ensembled deep learning model outperforms human experts in diagnosing biliary atresia from sonographic gallbladder images.

Nature communications
It is still challenging to make accurate diagnosis of biliary atresia (BA) with sonographic gallbladder images particularly in rural area without relevant expertise. To help diagnose BA based on sonographic gallbladder images, an ensembled deep learn...