AIMC Topic: Image Interpretation, Computer-Assisted

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Deep Learning Approaches Towards Skin Lesion Segmentation and Classification from Dermoscopic Images - A Review.

Current medical imaging
BACKGROUND: Automated intelligent systems for unbiased diagnosis are primary requirement for the pigment lesion analysis. It has gained the attention of researchers in the last few decades. These systems involve multiple phases such as pre-processing...

Integrating Convolutional Neural Networks and Multi-Task Dictionary Learning for Cognitive Decline Prediction with Longitudinal Images.

Journal of Alzheimer's disease : JAD
BACKGROUND: Disease progression prediction based on neuroimaging biomarkers is vital in Alzheimer's disease (AD) research. Convolutional neural networks (CNN) have been proved to be powerful for various computer vision research by refining reliable a...

Updating Diagnoses for Speed and Accuracy: Using AI, Cameras, Assays, and More.

IEEE pulse
When it comes to their health, people want answers right now. But clinicians cannot always make snap judgments about ailments or injuries. One way to help both general practitioners and patients is to introduce technologies that deliver quick and acc...

Assessment of mental workload based on multi-physiological signals.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Mental workload is one of the contributing factors to human errors in road accidents or other potentially adverse incidents.

Diagnostic Performance of the Support Vector Machine Model for Breast Cancer on Ring-Shaped Dedicated Breast Positron Emission Tomography Images.

Journal of computer assisted tomography
OBJECTIVE: The aim of this study was to evaluate the diagnostic ability of support vector machine (SVM) for early breast cancer (BC) using dedicated breast positron emission tomography (dbPET).

Automatic left ventricle segmentation from cardiac magnetic resonance images using a capsule network.

Journal of X-ray science and technology
PURPOSE: Segmentation of magnetic resonance images (MRI) of the left ventricle (LV) plays a key role in quantifying the volumetric functions of the heart, such as the area, volume, and ejection fraction. Traditionally, LV segmentation is performed ma...

The Path to and Impact of Disease Recognition with AI.

IEEE pulse
The Process of rare disease identification by clinical geneticists is closely associated with the ability to correlate the phenotype of a patient with the relevant genetic syndromes. In order to perform this correlation, the phenotype has to be descr...

Deep Learning Technique for Musculoskeletal Analysis.

Advances in experimental medicine and biology
Advancements in musculoskeletal analysis have been achieved by adopting deep learning technology in image recognition and analysis. Unlike musculoskeletal modeling based on computational anatomy, deep learning-based methods can obtain muscle informat...

Deep Learning Computer-Aided Diagnosis for Breast Lesion in Digital Mammogram.

Advances in experimental medicine and biology
For computer-aided diagnosis (CAD), detection, segmentation, and classification from medical imagery are three key components to efficiently assist physicians for accurate diagnosis. In this chapter, a completely integrated CAD system based on deep l...

Deep Learning for Pulmonary Image Analysis: Classification, Detection, and Segmentation.

Advances in experimental medicine and biology
Image-based computer-aided diagnosis (CAD) algorithms by the use of convolutional neural network (CNN) which do not require the image-feature extractor are powerful compared with conventional feature-based CAD algorithms which require the image-featu...