AIMC Topic: Retrospective Studies

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Fully Automated MRI Segmentation and Volumetric Measurement of Intracranial Meningioma Using Deep Learning.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Accurate and rapid measurement of the MRI volume of meningiomas is essential in clinical practice to determine the growth rate of the tumor. Imperfect automation and disappointing performance for small meningiomas of previous automated vo...

Deep Learning-Enhanced Parallel Imaging and Simultaneous Multislice Acceleration Reconstruction in Knee MRI.

Investigative radiology
OBJECTIVES: This study aimed to examine various combinations of parallel imaging (PI) and simultaneous multislice (SMS) acceleration imaging using deep learning (DL)-enhanced and conventional reconstruction. The study also aimed at comparing the diag...

Combined diagnosis of multiparametric MRI-based deep learning models facilitates differentiating triple-negative breast cancer from fibroadenoma magnetic resonance BI-RADS 4 lesions.

Journal of cancer research and clinical oncology
PURPOSE: To investigate the value of the combined diagnosis of multiparametric MRI-based deep learning models to differentiate triple-negative breast cancer (TNBC) from fibroadenoma magnetic resonance Breast Imaging-Reporting and Data System category...

Clinical feasibility of accelerated diffusion weighted imaging of the abdomen with deep learning reconstruction: Comparison with conventional diffusion weighted imaging.

European journal of radiology
PURPOSE: To assess the clinical feasibility of accelerated deep learning-reconstructed diffusion weighted imaging (DWI) and to compare its image quality and acquisition time with those of conventional DWI.

Comparison of skeletal segmentation by deep learning-based and atlas-based segmentation in prostate cancer patients.

Annals of nuclear medicine
OBJECTIVE: We aimed to compare the deep learning-based (VSBONE BSI) and atlas-based (BONENAVI) segmentation accuracy that have been developed to measure the bone scan index based on skeletal segmentation.

LRFNet: A deep learning model for the assessment of liver reserve function based on Child-Pugh score and CT image.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Liver reserve function should be accurately evaluated in patients with hepatic cellular cancer before surgery to evaluate the degree of liver tolerance to surgical methods. Meanwhile, liver reserve function is also an import...

The effectiveness of extremely low-pressure pneumoperitoneum on pain reduction after robot-assisted cholecystectomy.

Asian journal of surgery
BACKGROUND: The robot-assisted cholecystectomy could provide a sufficient surgical field with the extremely low-pressure pneumoperitoneum (ELPP; 4 mmHg) by the robot arm lifting the abdominal wall upward. This study aimed to investigate the effect of...

Added value of an artificial intelligence solution for fracture detection in the radiologist's daily trauma emergencies workflow.

Diagnostic and interventional imaging
PURPOSE: The main objective of this study was to compare radiologists' performance without and with artificial intelligence (AI) assistance for the detection of bone fractures from trauma emergencies.

Learning curve analysis of multiport robot-assisted hysterectomy.

Archives of gynecology and obstetrics
PURPOSE: The purpose of this study was to evaluate the surgical outcomes and learning curve of multiport robot-assisted hysterectomy.

Robot-Assisted Radical Prostatectomy After Prior Transurethral Resection of Prostate: An Analysis of Perioperative, Functional, Pathologic, and Oncologic Outcomes.

Journal of endourology
We performed a retrospective comparison of surgical, oncologic, and functional outcomes after robot-assisted radical prostatectomy between patients who have undergone prior transurethral resection of prostate (TURP) to TURP-naive patients. Past rob...