AIMC Topic: Deep Learning

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Leader-Based Multi-Scale Attention Deep Architecture for Person Re-Identification.

IEEE transactions on pattern analysis and machine intelligence
Person re-identification (re-id) aims to match people across non-overlapping camera views in a public space. This is a challenging problem because the people captured in surveillance videos often wear similar clothing. Consequently, the differences i...

Enhancing images of shale formations by a hybrid stochastic and deep learning algorithm.

Neural networks : the official journal of the International Neural Network Society
Accounting for the morphology of shale formations, which represent highly heterogeneous porous media, is a difficult problem. Although two- or three-dimensional images of such formations may be obtained and analyzed, they either do not capture the na...

Accurate and robust deep learning-based segmentation of the prostate clinical target volume in ultrasound images.

Medical image analysis
The goal of this work was to develop a method for accurate and robust automatic segmentation of the prostate clinical target volume in transrectal ultrasound (TRUS) images for brachytherapy. These images can be difficult to segment because of weak or...

Clinical-grade computational pathology using weakly supervised deep learning on whole slide images.

Nature medicine
The development of decision support systems for pathology and their deployment in clinical practice have been hindered by the need for large manually annotated datasets. To overcome this problem, we present a multiple instance learning-based deep lea...

Development and Evaluation of ClientBot: Patient-Like Conversational Agent to Train Basic Counseling Skills.

Journal of medical Internet research
BACKGROUND: Training therapists is both expensive and time-consuming. Degree-based training can require tens of thousands of dollars and hundreds of hours of expert instruction. Counseling skills practice often involves role-plays, standardized patie...

Automated identification of malignancy in whole-slide pathological images: identification of eyelid malignant melanoma in gigapixel pathological slides using deep learning.

The British journal of ophthalmology
BACKGROUND/AIMS: To develop a deep learning system (DLS) that can automatically detect malignant melanoma (MM) in the eyelid from histopathological sections with colossal information density.

Automated deep learning method for whole-breast segmentation in diffusion-weighted breast MRI.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Diffusion-weighted imaging (DWI) in MRI plays an increasingly important role in diagnostic applications and developing imaging biomarkers. Automated whole-breast segmentation is an important yet challenging step for quantitative breast im...

The Application of Deep Learning in the Risk Grading of Skin Tumors for Patients Using Clinical Images.

Journal of medical systems
According to diagnostic criteria, skin tumors can be divided into three categories: benign, low degree and high degree malignancy. For high degree malignant skin tumors, if not detected in time, they can do serious harm to patients' health. However, ...

Thorax-Net: An Attention Regularized Deep Neural Network for Classification of Thoracic Diseases on Chest Radiography.

IEEE journal of biomedical and health informatics
Deep learning techniques have been increasingly used to provide more accurate and more accessible diagnosis of thorax diseases on chest radiographs. However, due to the lack of dense annotation of large-scale chest radiograph data, this computer-aide...