AIMC Topic: Image Processing, Computer-Assisted

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Self-derived organ attention for unpaired CT-MRI deep domain adaptation based MRI segmentation.

Physics in medicine and biology
To develop and evaluate a deep learning method to segment parotid glands from MRI using unannotated MRI and unpaired expert-segmented CT datasets. We introduced a new self-derived organ attention deep learning network for combined CT to MRI image-to-...

Issues associated with deploying CNN transfer learning to detect COVID-19 from chest X-rays.

Physical and engineering sciences in medicine
Covid-19 first occurred in Wuhan, China in December 2019. Subsequently, the virus spread throughout the world and as of June 2020 the total number of confirmed cases are above 4.7 million with over 315,000 deaths. Machine learning algorithms built on...

Estimating 3-dimensional liver motion using deep learning and 2-dimensional ultrasound images.

International journal of computer assisted radiology and surgery
PURPOSE: The main purpose of this study is to construct a system to track the tumor position during radiofrequency ablation (RFA) treatment. Existing tumor tracking systems are designed to track a tumor in a two-dimensional (2D) ultrasound (US) image...

Technical Note: Automatic segmentation of CT images for ventral body composition analysis.

Medical physics
PURPOSE: Body composition is known to be associated with many diseases including diabetes, cancers, and cardiovascular diseases. In this paper, we developed a fully automatic body tissue decomposition procedure to segment three major compartments tha...

Deep-learning-based enhanced optic-disc photography.

PloS one
Optic-disc photography (ODP) has proven to be very useful for optic nerve evaluation in glaucoma. In real clinical practice, however, limited patient cooperation, small pupils, or media opacities can limit the performance of ODP. The purpose of this ...

Difficulty-aware hierarchical convolutional neural networks for deformable registration of brain MR images.

Medical image analysis
The aim of deformable brain image registration is to align anatomical structures, which can potentially vary with large and complex deformations. Anatomical structures vary in size and shape, requiring the registration algorithm to estimate deformati...

Accelerating T mapping of the brain by integrating deep learning priors with low-rank and sparse modeling.

Magnetic resonance in medicine
PURPOSE: To accelerate T mapping with highly sparse sampling by integrating deep learning image priors with low-rank and sparse modeling.

Bruise dating using deep learning.

Journal of forensic sciences
The bruise dating can have important medicolegal implications in family violence and violence against women cases. However, studies show that the medical specialist has 50% accuracy in classifying a bruise by age, mainly due to the variability of the...

An entropy-based approach to detect and localize intraoperative bleeding during minimally invasive surgery.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: During minimally invasive surgery (either robotic or traditional laparoscopic), vascular injuries may occur because of inadvertent surgical tool movements or actions. These vascular injuries can lead to arterial or venous bleeding with va...