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Pelvis

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Transforming UTE-mDixon MR Abdomen-Pelvis Images Into CT by Jointly Leveraging Prior Knowledge and Partial Supervision.

IEEE/ACM transactions on computational biology and bioinformatics
Computed tomography (CT) provides information for diagnosis, PET attenuation correction (AC), and radiation treatment planning (RTP). Disadvantages of CT include poor soft tissue contrast and exposure to ionizing radiation. While MRI can overcome the...

Contemporary National Trends and Variations of Pelvic Lymph Node Dissection in Patients Undergoing Robot-Assisted Radical Prostatectomy.

Clinical genitourinary cancer
INTRODUCTION: Previous studies showed suboptimal adherence to clinical practice guidelines for pelvic lymph node dissection (PLND) during radical prostatectomy (RP). Robot-assisted RP (RARP) has become the predominant surgical management for localize...

Multi-task edge-recalibrated network for male pelvic multi-organ segmentation on CT images.

Physics in medicine and biology
Automated male pelvic multi-organ segmentation on CT images is highly desired for applications, including radiotherapy planning. To further improve the performance and efficiency of existing automated segmentation methods, in this study, we propose a...

An Automated Deep Learning Method for Tile AO/OTA Pelvic Fracture Severity Grading from Trauma whole-Body CT.

Journal of digital imaging
Admission trauma whole-body CT is routinely employed as a first-line diagnostic tool for characterizing pelvic fracture severity. Tile AO/OTA grade based on the presence or absence of rotational and translational instability corresponds with need for...

A deep learning approach to generate synthetic CT in low field MR-guided adaptive radiotherapy for abdominal and pelvic cases.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
PURPOSE: Artificial intelligence (AI) can play a significant role in Magnetic Resonance guided Radiotherapy (MRgRT), especially to speed up the online adaptive workflow. The aim of this study is to set up a Deep Learning (DL) approach able to generat...

Complete abdomen and pelvis segmentation using U-net variant architecture.

Medical physics
PURPOSE: Organ segmentation of computed tomography (CT) imaging is essential for radiotherapy treatment planning. Treatment planning requires segmentation not only of the affected tissue, but nearby healthy organs-at-risk, which is laborious and time...

On the use of machine learning algorithms in forensic anthropology.

Legal medicine (Tokyo, Japan)
The classification performance of the statistical methods binary logistic regression (BLR), multinomial and penalized multinomial logistic regression (MLR, pMLR), linear discriminant analysis (LDA), and the machine learning algorithms naïve Bayes cla...

The effect of deep convolutional neural networks on radiologists' performance in the detection of hip fractures on digital pelvic radiographs.

European journal of radiology
PURPOSE: The purpose of our study is to develop deep convolutional neural network (DCNN) for detecting hip fractures using CT and MRI as a gold standard, and to evaluate the diagnostic performance of 7 readers with and without DCNN.

Impact of indocyanine green-guided extended pelvic lymph node dissection during robot-assisted radical prostatectomy.

International journal of urology : official journal of the Japanese Urological Association
OBJECTIVES: To evaluate the effectiveness of indocyanine green-guided extended pelvic lymph node dissection during robot-assisted radical prostatectomy for intermediate- to high-risk prostate cancer.