AIMC Topic: Image Processing, Computer-Assisted

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Convolution neural network for effective burn region segmentation of color images.

Burns : journal of the International Society for Burn Injuries
BACKGROUND: Burn injuries are one of the most severe forms of wounds and trauma across the globe. Automated burn diagnosis methods are needed to provide timely treatment to the concerned patients. Artificial intelligence is playing a vital role in de...

Image manipulation with natural language using Two-sided Attentive Conditional Generative Adversarial Network.

Neural networks : the official journal of the International Neural Network Society
Altering the content of an image with photo editing tools is a tedious task for an inexperienced user, especially, when modifying the visual attributes of a specific object in an image without affecting other constituents such as background etc. To s...

Skeletal bone age prediction based on a deep residual network with spatial transformer.

Computer methods and programs in biomedicine
OBJECTIVE: Bone age prediction can be performed by medical experts manually assessment of X-ray images of the hand bone. In practice, the workload is huge, resource consumption is large, measurement takes a long time, and it is easily influenced by h...

Application of hierarchical clustering to multi-parametric MR in prostate: Differentiation of tumor and normal tissue with high accuracy.

Magnetic resonance imaging
PURPOSE: Hierarchical clustering (HC), an unsupervised machine learning (ML) technique, was applied to multi-parametric MR (mp-MR) for prostate cancer (PCa). The aim of this study is to demonstrate HC can diagnose PCa in a straightforward interpretab...

Comparison of performances of conventional and deep learning-based methods in segmentation of lung vessels and registration of chest radiographs.

Radiological physics and technology
Conventional machine learning-based methods have been effective in assisting physicians in making accurate decisions and utilized in computer-aided diagnosis for more than 30 years. Recently, deep learning-based methods, and convolutional neural netw...

Cardiac magnetic resonance image segmentation based on convolutional neural network.

Computer methods and programs in biomedicine
OBJECTIVE: In cardiac medical imaging, the extraction and segmentation of the part of interest is the key to the diagnosis of heart disease. Due to irregular diastole and contraction, magnetic resonance imaging (MRI) images have poorly defined bounda...

4D-AirNet: a temporally-resolved CBCT slice reconstruction method synergizing analytical and iterative method with deep learning.

Physics in medicine and biology
Four-dimensional (4D) cone-beam CT (CBCT) reconstructs temporally-resolved phases of 3D volumes often with the same amount of projection data that are meant for reconstructing a single 3D volume. 4D CBCT is a sparse-data problem that is very challeng...

Person identification from EEG using various machine learning techniques with inter-hemispheric amplitude ratio.

PloS one
Association between electroencephalography (EEG) and individually personal information is being explored by the scientific community. Though person identification using EEG is an attraction among researchers, the complexity of sensing limits using su...

Interactive machine learning for fast and robust cell profiling.

PloS one
Automated profiling of cell morphology is a powerful tool for inferring cell function. However, this technique retains a high barrier to entry. In particular, configuring image processing parameters for optimal cell profiling is susceptible to cognit...