AIMC Topic: Cicatrix

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Artificial Intelligence Assessment of Renal Scarring (AIRS Study).

Kidney360
BACKGROUND: The goal of the Artificial Intelligence in Renal Scarring (AIRS) study is to develop machine learning tools for noninvasive quantification of kidney fibrosis from imaging scans.

Deep learning to diagnose pouch of Douglas obliteration with ultrasound sliding sign.

Reproduction & fertility
OBJECTIVES: Pouch of Douglas (POD) obliteration is a severe consequence of inflammation in the pelvis, often seen in patients with endometriosis. The sliding sign is a dynamic transvaginal ultrasound (TVS) test that can diagnose POD obliteration. We ...

Multidisciplinary Approach to Robotic Resection of Abdominal Wall Endometriosis and Mesh Repair.

Journal of minimally invasive gynecology
STUDY OBJECTIVE: To demonstrate a technique for robot-assisted laparoscopic excision of abdominal wall endometriosis and mesh reinforcement of the subsequent defect.

Cesarean scar pregnancy: Reproductive outcome after robotic laparoscopic removal with simultaneous repair of the uterine defect.

European journal of obstetrics, gynecology, and reproductive biology
OBJECTIVE: To describe perioperative adverse events, fertility and obstetric outcome, following a robot assisted laparoscopic approach for treating Cesarean scar pregnancies (CSP).

Improved Quantification of Myocardium Scar in Late Gadolinium Enhancement Images: Deep Learning Based Image Fusion Approach.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Quantification of myocardium scarring in late gadolinium enhanced (LGE) cardiac magnetic resonance imaging can be challenging due to low scar-to-background contrast and low image quality. To resolve ambiguous LGE regions, experienced read...

Robotic CSP Resection and Hysterotomy Repair.

Journal of minimally invasive gynecology
STUDY OBJECTIVE: To demonstrate a technique for the robot-assisted laparoscopic surgical management of cesarean section scar ectopic pregnancy (CSP) and hysterotomy repair.

Improvement of late gadolinium enhancement image quality using a deep learning-based reconstruction algorithm and its influence on myocardial scar quantification.

European radiology
OBJECTIVES: The aim of this study was to assess the effect of a deep learning (DL)-based reconstruction algorithm on late gadolinium enhancement (LGE) image quality and to evaluate its influence on scar quantification.

Detecting myocardial scar using electrocardiogram data and deep neural networks.

Biological chemistry
Ischaemic heart disease is among the most frequent causes of death. Early detection of myocardial pathologies can increase the benefit of therapy and reduce the number of lethal cases. Presence of myocardial scar is an indicator for developing ischae...