AIMC Topic: Software

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SpeckleGAN: a generative adversarial network with an adaptive speckle layer to augment limited training data for ultrasound image processing.

International journal of computer assisted radiology and surgery
PURPOSE: In the field of medical image analysis, deep learning methods gained huge attention over the last years. This can be explained by their often improved performance compared to classic explicit algorithms. In order to work well, they need larg...

KAML: improving genomic prediction accuracy of complex traits using machine learning determined parameters.

Genome biology
Advances in high-throughput sequencing technologies have reduced the cost of genotyping dramatically and led to genomic prediction being widely used in animal and plant breeding, and increasingly in human genetics. Inspired by the efficient computing...

Meta-iPVP: a sequence-based meta-predictor for improving the prediction of phage virion proteins using effective feature representation.

Journal of computer-aided molecular design
Phage virion protein (PVP) perforate the host cell membrane and eventually culminates in cell rupture thereby releasing replicated phages. The accurate identification of PVP is thus a crucial step towards improving our understanding of the biological...

Artificial intelligence: improving the efficiency of cardiovascular imaging.

Expert review of medical devices
INTRODUCTION: Artificial intelligence (AI) describes the use of computational techniques to mimic human intelligence. In healthcare, this typically involves large medical datasets being used to predict a diagnosis, identify new disease genotypes or p...

Real-Time Selective Markerless Tracking of Forepaws of Head Fixed Mice Using Deep Neural Networks.

eNeuro
Here, we describe a system capable of tracking specific mouse paw movements at high frame rates (70.17 Hz) with a high level of accuracy (mean=0.95, SD<0.01). Short-latency markerless tracking of specific body parts opens up the possibility of manipu...

Deep-Learning F-FDG Uptake Classification Enables Total Metabolic Tumor Volume Estimation in Diffuse Large B-Cell Lymphoma.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Total metabolic tumor volume (TMTV), calculated from F-FDG PET/CT baseline studies, is a prognostic factor in diffuse large B-cell lymphoma (DLBCL) whose measurement requires the segmentation of all malignant foci throughout the body. No consensus cu...

R-ELMNet: Regularized extreme learning machine network.

Neural networks : the official journal of the International Neural Network Society
Principal component analysis network (PCANet), as an unsupervised shallow network, demonstrates noticeable effectiveness on datasets of various volumes. It carries a two-layer convolution with PCA as filter learning method, followed by a block-wise h...

A network-based computational framework to predict and differentiate functions for gene isoforms using exon-level expression data.

Methods (San Diego, Calif.)
MOTIVATION: Alternative splicing makes significant contributions to functional diversity of transcripts and proteins. Many alternatively spliced gene isoforms have been shown to perform specific biological functions under different contexts. In addit...

FastSurfer - A fast and accurate deep learning based neuroimaging pipeline.

NeuroImage
Traditional neuroimage analysis pipelines involve computationally intensive, time-consuming optimization steps, and thus, do not scale well to large cohort studies with thousands or tens of thousands of individuals. In this work we propose a fast and...