AIMC Topic: Humans

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Assessing the Effects of Deep Learning Reconstruction on Abdominal CT Without Arm Elevation.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
To evaluate the effects of deep learning reconstruction (DLR) on image quality of abdominal computed tomography (CT) in patients without arm elevation compared with hybrid-iterative reconstruction (Hybrid-IR) and filtered back projection (FBP). In ...

Automated Triage of Screening Breast MRI Examinations in High-Risk Women Using an Ensemble Deep Learning Model.

Investigative radiology
OBJECTIVES: The aim of the study is to develop and evaluate the performance of a deep learning (DL) model to triage breast magnetic resonance imaging (MRI) findings in high-risk patients without missing any cancers.

Pie-Net: Prior-information-enabled deep learning noise reduction for coronary CT angiography acquired with a photon counting detector CT.

Medical physics
BACKGROUND: Photon-counting-detector CT (PCD-CT) enables the production of virtual monoenergetic images (VMIs) at a high spatial resolution (HR) via simultaneous acquisition of multi-energy data. However, noise levels in these HR VMIs are markedly in...

Artificial Intelligence and Interstitial Lung Disease: Diagnosis and Prognosis.

Investigative radiology
Interstitial lung disease (ILD) is now diagnosed by an ILD-board consisting of radiologists, pulmonologists, and pathologists. They discuss the combination of computed tomography (CT) images, pulmonary function tests, demographic information, and his...

Robot-assisted Laparoscopic Urethral Diverticulectomy in a Pediatric Patient.

Urology
Urethral diverticula are rare in children, especially in the absence of trauma. We present a case of a 9-year-old girl with pain with micturition, incontinence, and recurrent urinary tract infections. Diagnosis of urethral diverticulum was made by ma...

Use of the Globus ExcelsiusGPS System for Robotic Stereoelectroencephalography: An Initial Experience.

World neurosurgery
BACKGROUND: Stereoelectroencephalography (SEEG) is a critical tool used in the identification of epileptogenic zones. Although stereotactic frame-based SEEG procedures have been performed traditionally, newer robotic-assisted SEEG procedures have bec...

Adoption of Robotic Adrenalectomy: A Two-Institution Study of Surgeon Learning Curve.

Annals of surgical oncology
BACKGROUND: Robotic adrenalectomy is feasible and safe, yet concerns over increased operative times and the learning curve (LC) for proficiency have limited its adoption. This study aimed to assess the LC for robotic adrenalectomy.