AIMC Topic: Image Processing, Computer-Assisted

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Alcoholism Detection by Data Augmentation and Convolutional Neural Network with Stochastic Pooling.

Journal of medical systems
Alcohol use disorder (AUD) is an important brain disease. It alters the brain structure. Recently, scholars tend to use computer vision based techniques to detect AUD. We collected 235 subjects, 114 alcoholic and 121 non-alcoholic. Among the 235 imag...

White blood cells identification system based on convolutional deep neural learning networks.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: White blood cells (WBCs) differential counting yields valued information about human health and disease. The current developed automated cell morphology equipments perform differential count which is based on blood smear im...

Convolutional neural network-based malaria diagnosis from focus stack of blood smear images acquired using custom-built slide scanner.

Journal of biophotonics
The present paper introduces a focus stacking-based approach for automated quantitative detection of Plasmodium falciparum malaria from blood smear. For the detection, a custom designed convolutional neural network (CNN) operating on focus stack of i...

Learning normalized inputs for iterative estimation in medical image segmentation.

Medical image analysis
In this paper, we introduce a simple, yet powerful pipeline for medical image segmentation that combines Fully Convolutional Networks (FCNs) with Fully Convolutional Residual Networks (FC-ResNets). We propose and examine a design that takes particula...

Foreground Detection by Competitive Learning for Varying Input Distributions.

International journal of neural systems
One of the most important challenges in computer vision applications is the background modeling, especially when the background is dynamic and the input distribution might not be stationary, i.e. the distribution of the input data could change with t...

Image processing strategies based on saliency segmentation for object recognition under simulated prosthetic vision.

Artificial intelligence in medicine
BACKGROUND AND OBJECTIVE: Current retinal prostheses can only generate low-resolution visual percepts constituted of limited phosphenes which are elicited by an electrode array and with uncontrollable color and restricted grayscale. Under this visual...

Learning a variational network for reconstruction of accelerated MRI data.

Magnetic resonance in medicine
PURPOSE: To allow fast and high-quality reconstruction of clinical accelerated multi-coil MR data by learning a variational network that combines the mathematical structure of variational models with deep learning.

Radiomics and radiogenomics in lung cancer: A review for the clinician.

Lung cancer (Amsterdam, Netherlands)
Lung cancer is responsible for a large proportion of cancer-related deaths across the globe, with delayed detection being perhaps the most significant factor for its high mortality rate. Though the National Lung Screening Trial argues for screening o...

High Performance Implementation of 3D Convolutional Neural Networks on a GPU.

Computational intelligence and neuroscience
Convolutional neural networks have proven to be highly successful in applications such as image classification, object tracking, and many other tasks based on 2D inputs. Recently, researchers have started to apply convolutional neural networks to vid...

Digital image analysis in breast pathology-from image processing techniques to artificial intelligence.

Translational research : the journal of laboratory and clinical medicine
Breast cancer is the most common malignant disease in women worldwide. In recent decades, earlier diagnosis and better adjuvant therapy have substantially improved patient outcome. Diagnosis by histopathology has proven to be instrumental to guide br...