AIMC Topic: Rectum
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Multi-atlas and unsupervised learning approach to perirectal space segmentation in CT images.
Australasian physical & engineering sciences in medicine
Nov 14, 2016
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
Oct 15, 2016
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...
Hartmann's procedure vs abdominoperineal resection with intersphincteric dissection in patients with rectal cancer: a randomized multicentre trial (HAPIrect).
BMC surgery
Jul 11, 2016
BACKGROUND: The use of Hartmann's procedure in the old and frail and/or in patients with fecal incontinence is increasing, even though some data have reported high postoperative rates of pelvic abscesses. Abdominoperineal excision with intersphincter...
Accurate Segmentation of CT Male Pelvic Organs via Regression-Based Deformable Models and Multi-Task Random Forests.
IEEE transactions on medical imaging
Jan 18, 2016
Segmenting male pelvic organs from CT images is a prerequisite for prostate cancer radiotherapy. The efficacy of radiation treatment highly depends on segmentation accuracy. However, accurate segmentation of male pelvic organs is challenging due to l...
Quantitative assessment of colorectal morphology: Implications for robotic colonoscopy.
Medical engineering & physics
Jan 4, 2016
This paper presents a method of characterizing the distribution of colorectal morphometrics. It uses three-dimensional region growing and topological thinning algorithms to determine and visualize the luminal volume and centreline of the colon, respe...
Robot-assisted surgery for the radical treatment of deep infiltrating endometriosis with colorectal involvement: short- and mid-term surgical and functional outcomes.
International journal of colorectal disease
Dec 21, 2015
PURPOSE: Sexual and urinary dysfunctions are complications in radical treatment of deep infiltrating endometriosis (DIE) with colorectal involvement. The aim of this article is to report the preliminary results of our single-institution experience wi...
Knowledge-based radiation therapy (KBRT) treatment planning versus planning by experts: validation of a KBRT algorithm for prostate cancer treatment planning.
Radiation oncology (London, England)
May 10, 2015
BACKGROUND: A knowledge-based radiation therapy (KBRT) treatment planning algorithm was recently developed. The purpose of this work is to investigate how plans that are generated with the objective KBRT approach compare to those that rely on the jud...
Utilization of a novel valveless trocar system during robotic-assisted laparoscopic prostatectomy.
World journal of urology
Mar 1, 2015
PURPOSE: To evaluate the effect of a novel valveless trocar system (VTS) on perioperative outcomes in patients undergoing robotic-assisted laparoscopic prostatectomy (RALP).
Learning curve for robotic-assisted surgery for rectal cancer: use of the cumulative sum method.
Surgical endoscopy
Oct 3, 2014
BACKGROUND: Few data are available to assess the learning curve for robotic-assisted surgery for rectal cancer. The aim of the present study was to evaluate the learning curve for robotic-assisted surgery for rectal cancer by a surgeon at a single in...
Serum calcium-based interpretable machine learning model for predicting anastomotic leakage after rectal cancer resection: A multi-center study.
World journal of gastroenterology
May 21, 2025
BACKGROUND: Despite the promising prospects of utilizing artificial intelligence and machine learning (ML) for comprehensive disease analysis, few models constructed have been applied in clinical practice due to their complexity and the lack of reaso...
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