AIMC Topic: Retrospective Studies

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Deep neural network for automatic volumetric segmentation of whole-body CT images for body composition assessment.

Clinical nutrition (Edinburgh, Scotland)
BACKGROUND & AIMS: Body composition analysis on CT images is a valuable tool for sarcopenia assessment. We aimed to develop and validate a deep neural network applicable to whole-body CT images of PET-CT scan for the automatic volumetric segmentation...

Development of MRI-Based Radiomics Model to Predict the Risk of Recurrence in Patients With Advanced High-Grade Serous Ovarian Carcinoma.

AJR. American journal of roentgenology
The purpose of our study was to develop a radiomics model based on preoperative MRI and clinical information for predicting recurrence-free survival (RFS) in patients with advanced high-grade serous ovarian carcinoma (HGSOC). This retrospective stu...

High through-plane resolution CT imaging with self-supervised deep learning.

Physics in medicine and biology
CT images for radiotherapy planning are usually acquired in thick slices to reduce the imaging dose, especially for pediatric patients, and to lessen the need for contouring and treatment planning on more slices. However, low through-plane resolution...

Robotic guidance platform for laser interstitial thermal ablation and stereotactic needle biopsies: a single center experience.

Journal of robotic surgery
While laser ablation has become an increasingly important tool in the neurosurgical oncologist's armamentarium, deep seated lesions, and those located near critical structures require utmost accuracy during stereotactic laser catheter placement. Robo...

Convolutional Neural Network of Multiparametric MRI Accurately Detects Axillary Lymph Node Metastasis in Breast Cancer Patients With Pre Neoadjuvant Chemotherapy.

Clinical breast cancer
BACKGROUND: Accurate assessment of the axillary lymph nodes (aLNs) in breast cancer patients is essential for prognosis and treatment planning. Current radiological staging of nodal metastasis has poor accuracy. This study aimed to investigate the ma...

Accelerate gas diffusion-weighted MRI for lung morphometry with deep learning.

European radiology
OBJECTIVES: Multiple b-value gas diffusion-weighted MRI (DW-MRI) enables non-invasive and quantitative assessment of lung morphometry, but its long acquisition time is not well-tolerated by patients. We aimed to accelerate multiple b-value gas DW-MRI...

Outcomes of robot-assisted urinary sphincter implantation for male neurogenic urinary incontinence.

BJU international
OBJECTIVES: To report the functional outcomes of robot-assisted laparoscopic artificial urinary sphincter implantation (R-AUS) in men with neurogenic stress urinary incontinence (SUI).

Initial Experience with Robotic Inguinal Hernia Repair in the Adolescent Population.

Journal of laparoendoscopic & advanced surgical techniques. Part A
There is no one standard procedure encompassing the needs and differences of the entire pediatric population for inguinal hernia repair (IHR). Several techniques can be used, including open repair, laparoscopic, and robotic-assisted laparoscopic rep...

Automatic Classification of the Korean Triage Acuity Scale in Simulated Emergency Rooms Using Speech Recognition and Natural Language Processing: a Proof of Concept Study.

Journal of Korean medical science
BACKGROUND: Rapid triage reduces the patients' stay time at an emergency department (ED). The Korean Triage Acuity Scale (KTAS) is mandatorily applied at EDs in South Korea. For rapid triage, we studied machine learning-based triage systems composed ...

Deep Learning Network for Segmentation of the Prostate Gland With Median Lobe Enlargement in T2-weighted MR Images: Comparison With Manual Segmentation Method.

Current problems in diagnostic radiology
PURPOSE: Aim of this study was to evaluate a fully automated deep learning network named Efficient Neural Network (ENet) for segmentation of prostate gland with median lobe enlargement compared to manual segmentation.