AI Medical Compendium Topic

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Rectum

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Machine Learning-based Analysis of Rectal Cancer MRI Radiomics for Prediction of Metachronous Liver Metastasis.

Academic radiology
RATIONALE AND OBJECTIVES: To use machine learning-based magnetic resonance imaging radiomics to predict metachronous liver metastases (MLM) in patients with rectal cancer.

Predicting survival from colorectal cancer histology slides using deep learning: A retrospective multicenter study.

PLoS medicine
BACKGROUND: For virtually every patient with colorectal cancer (CRC), hematoxylin-eosin (HE)-stained tissue slides are available. These images contain quantitative information, which is not routinely used to objectively extract prognostic biomarkers....

Fully automated diagnostic system with artificial intelligence using endocytoscopy to identify the presence of histologic inflammation associated with ulcerative colitis (with video).

Gastrointestinal endoscopy
BACKGROUND AND AIMS: In the treatment of ulcerative colitis (UC), an incremental benefit of achieving histologic healing beyond that of endoscopic mucosal healing has been suggested; persistent histologic inflammation increases the risk of exacerbati...

Experimental infection of Friesian bulls with Theileria orientalis (Ikeda) and effects on the haematocrit, live weight, rectal temperature and activity.

Veterinary parasitology, regional studies and reports
Since 2012, New Zealand has suffered from an epidemic of infectious bovine anaemia associated with T. orientalis (Ikeda), an obligate intracellular protozoan parasite of cattle. Despite widespread agreement that T. orientalis (Ikeda) infection has im...

Technical Note: A deep learning-based autosegmentation of rectal tumors in MR images.

Medical physics
PURPOSE: Manual contouring of gross tumor volumes (GTV) is a crucial and time-consuming process in rectum cancer radiotherapy. This study aims to develop a simple deep learning-based autosegmentation algorithm to segment rectal tumors on T2-weighted ...

Deep convolutional neural network with transfer learning for rectum toxicity prediction in cervical cancer radiotherapy: a feasibility study.

Physics in medicine and biology
Better understanding of the dose-toxicity relationship is critical for safe dose escalation to improve local control in late-stage cervical cancer radiotherapy. In this study, we introduced a convolutional neural network (CNN) model to analyze rectum...

Clinical implementation of a knowledge based planning tool for prostate VMAT.

Radiation oncology (London, England)
BACKGROUND: A knowledge based planning tool has been developed and implemented for prostate VMAT radiotherapy plans providing a target average rectum dose value based on previously achievable values for similar rectum/PTV overlap. The purpose of this...

Multi-atlas and unsupervised learning approach to perirectal space segmentation in CT images.

Australasian physical & engineering sciences in medicine
Perirectal space segmentation in computed tomography images aids in quantifying radiation dose received by healthy tissues and toxicity during the course of radiation therapy treatment of the prostate. Radiation dose normalised by tissue volume facil...

Combined robotic transanal total mesorectal excision (R-taTME) and single-site plus one-port (R-SSPO) technique for ultra-low rectal surgery-initial experience with a new operation approach.

International journal of colorectal disease
OBJECTIVE: Robot-assisted rectal surgery is gaining popularity, and robotic single-site surgery is also being explored clinically. We report our initial experience with robotic transanal total mesorectal excision (R-taTME) and radical proctectomy usi...