The international journal of medical robotics + computer assisted surgery : MRCAS
Sep 8, 2020
BACKGROUND: We hypothesized that the total operative time of robot myomectomy (RM) is shorter than that of laparoscopic myomectomy (LM) in cases where numerous myomas are removed, due to the faster suturing time of the robotic system. To verify this,...
PURPOSE: To assess the performance of machine learning (ML)-based magnetic resonance imaging (MRI) radiomics analysis for discriminating between uveal melanoma (UM) and other intraocular masses.
Deep learning-based computer vision methods have recently made remarkable breakthroughs in the analysis and classification of cancer pathology images. However, there has been relatively little investigation of the utility of deep neural networks to s...
The successful development of the image denoising techniques for low-dose computed tomography (LDCT) was largely owing to the public-domain availability of spatially-aligned high- and low-dose CT image pairs. Even though low-dose CT scans are also hi...
Futurists have anticipated that novel autonomous technologies, embedded with machine learning (ML), will substantially influence healthcare. ML is focused on making predictions as accurate as possible, while traditional statistical models are aimed a...
Structural disorder is widespread in eukaryotic proteins and is vital for their function in diverse biological processes. It is therefore highly desirable to be able to predict the degree of order and disorder from amino acid sequence. It is, however...
BACKGROUND: Elbow imaging is challenging with conventional multidetector computed tomography (MDCT), while cone-beam CT (CBCT) provides superior options. We compared intra-individually CBCT versus MDCT image quality in cadaveric elbows.
The purpose of this work was to develop a deep learning (DL) based algorithm, Automatic intensity-modulated radiotherapy (IMRT) Planning via Static Field Fluence Prediction (AIP-SFFP), for automated prostate IMRT planning with real-time planning effi...
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