AIMC Topic: Image Processing, Computer-Assisted

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Skin Disease Recognition Method Based on Image Color and Texture Features.

Computational and mathematical methods in medicine
Skin diseases have a serious impact on people's life and health. Current research proposes an efficient approach to identify singular type of skin diseases. It is necessary to develop automatic methods in order to increase the accuracy of diagnosis f...

Breast Cancer Detection Using Infrared Thermal Imaging and a Deep Learning Model.

Sensors (Basel, Switzerland)
Women's breasts are susceptible to developing cancer; this is supported by a recent study from 2016 showing that 2.8 million women worldwide had already been diagnosed with breast cancer that year. The medical care of a patient with breast cancer is ...

Personalized Saliency and Its Prediction.

IEEE transactions on pattern analysis and machine intelligence
Nearly all existing visual saliency models by far have focused on predicting a universal saliency map across all observers. Yet psychology studies suggest that visual attention of different observers can vary significantly under specific circumstance...

Multimodal Assessment of Parkinson's Disease: A Deep Learning Approach.

IEEE journal of biomedical and health informatics
Parkinson's disease is a neurodegenerative disorder characterized by a variety of motor symptoms. Particularly, difficulties to start/stop movements have been observed in patients. From a technical/diagnostic point of view, these movement changes can...

An intelligent system for image-based rating of corrosion severity at stem taper of retrieved hip replacement implants.

Medical engineering & physics
Visual scoring of damage at taper junctions is the sole method to quantify corrosion in large-scale retrieval studies of failed hip replacement implants. This study introduces an intelligent image analysis-based method that objectively rates corrosio...

A Biologically Inspired Approach for Robot Depth Estimation.

Computational intelligence and neuroscience
Aimed at building autonomous service robots, reasoning, perception, and action should be properly integrated. In this paper, the depth cue has been analysed as an early stage given its importance for robotic tasks. So, from neuroscience findings, a h...

Deep Convolutional Neural Network Used in Single Sample per Person Face Recognition.

Computational intelligence and neuroscience
Face recognition (FR) with single sample per person (SSPP) is a challenge in computer vision. Since there is only one sample to be trained, it makes facial variation such as pose, illumination, and disguise difficult to be predicted. To overcome this...

Traditional machine learning for limited angle tomography.

International journal of computer assisted radiology and surgery
PURPOSE: The application of traditional machine learning techniques, in the form of regression models based on conventional, "hand-crafted" features, to artifact reduction in limited angle tomography is investigated.

Real-Time Deep Pose Estimation With Geodesic Loss for Image-to-Template Rigid Registration.

IEEE transactions on medical imaging
With an aim to increase the capture range and accelerate the performance of state-of-the-art inter-subject and subject-to-template 3-D rigid registration, we propose deep learning-based methods that are trained to find the 3-D position of arbitrarily...

Convolutional Neural Network Using a Breast MRI Tumor Dataset Can Predict Oncotype Dx Recurrence Score.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Oncotype Dx is a validated genetic analysis that provides a recurrence score (RS) to quantitatively predict outcomes in patients who meet the criteria of estrogen receptor positive / human epidermal growth factor receptor-2 negative (ER+/...