AIMC Topic: Algorithms

Clear Filters Showing 20021 to 20030 of 28713 articles

Attention gated networks: Learning to leverage salient regions in medical images.

Medical image analysis
We propose a novel attention gate (AG) model for medical image analysis that automatically learns to focus on target structures of varying shapes and sizes. Models trained with AGs implicitly learn to suppress irrelevant regions in an input image whi...

Acceleration of spleen segmentation with end-to-end deep learning method and automated pipeline.

Computers in biology and medicine
Delineation of Computed Tomography (CT) abdominal anatomical structure, specifically spleen segmentation, is useful for not only measuring tissue volume and biomarkers but also for monitoring interventions. Recently, segmentation algorithms using dee...

RAMS: Remote and automatic mammogram screening.

Computers in biology and medicine
About one in eight women in the U.S. will develop invasive breast cancer at some point in life. Breast cancer is the most common cancer found in women and if it is identified at an early stage by the use of mammograms, x-ray images of the breast, the...

Stock Market Forecasting Using Restricted Gene Expression Programming.

Computational intelligence and neuroscience
Stock index prediction is considered as a difficult task in the past decade. In order to predict stock index accurately, this paper proposes a novel prediction method based on S-system model. Restricted gene expression programming (RGEP) is proposed ...

An Effective Solution for Large Scale Single Machine Total Weighted Tardiness Problem using Lunar Cycle Inspired Artificial Bee Colony Algorithm.

IEEE/ACM transactions on computational biology and bioinformatics
Single machine total weighted tardiness problem (SMTWTP) is one of the fundamental combinatorial optimization problems. The problem consists of a set of independent jobs with distinct processing times, weights, and due dates to be scheduled on a sing...

Novel Regularization Method for Biomarker Selection and Cancer Classification.

IEEE/ACM transactions on computational biology and bioinformatics
Variable selection has attracted more attention in big data and machine learning fields. In high dimensional data analysis, many relevant variables or variable groups are widely found. For example, people pay more interests to biological pathway or r...

Learning a Probabilistic Model for Diffeomorphic Registration.

IEEE transactions on medical imaging
We propose to learn a low-dimensional probabilistic deformation model from data which can be used for the registration and the analysis of deformations. The latent variable model maps similar deformations close to each other in an encoding space. It ...

A structure-time parallel implementation of spike-based deep learning.

Neural networks : the official journal of the International Neural Network Society
Motivated by the recent progress of deep spiking neural networks (SNNs), we propose a structure-time parallel strategy based on layered structure and one-time computation over a time window to speed up the prominent spike-based deep learning algorith...

A Brain-Robot Interaction System by Fusing Human and Machine Intelligence.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
This paper presents a new brain-robot interaction system by fusing human and machine intelligence to improve the real-time control performance. This system consists of a hybrid P300 and steady-state visual evoked potential (SSVEP) mode conveying a hu...

An investigation of the effect of fat suppression and dimensionality on the accuracy of breast MRI segmentation using U-nets.

Medical physics
PURPOSE: Accurate segmentation of the breast is required for breast density estimation and the assessment of background parenchymal enhancement, both of which have been shown to be related to breast cancer risk. The MRI breast segmentation task is ch...