AIMC Topic: Deep Learning

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Deep learning detection of subtle fractures using staged algorithms to mimic radiologist search pattern.

Skeletal radiology
OBJECTIVE: To develop and evaluate a two-stage deep convolutional neural network system that mimics a radiologist's search pattern for detecting two small fractures: triquetral avulsion fractures and Segond fractures.

Novel deep learning-based noise reduction technique for prostate magnetic resonance imaging.

Abdominal radiology (New York)
INTRODUCTION: Magnetic resonance imaging (MRI) has played an increasingly major role in the evaluation of patients with prostate cancer, although prostate MRI presents several technical challenges. Newer techniques, such as deep learning (DL), have b...

Automatic screening of tear meniscus from lacrimal duct obstructions using anterior segment optical coherence tomography images by deep learning.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
PURPOSE: We assessed the ability of deep learning (DL) models to distinguish between tear meniscus of lacrimal duct obstruction (LDO) patients and normal subjects using anterior segment optical coherence tomography (ASOCT) images.

Proof of Concept for a Deep Learning Algorithm for Identification and Quantification of Key Microscopic Features in the Murine Model of DSS-Induced Colitis.

Toxicologic pathology
Inflammatory bowel disease (IBD) is a complex disease which leads to life-threatening complications and decreased quality of life. The dextran sulfate sodium (DSS) colitis model in mice is known for rapid screening of candidate compounds. Efficacy as...

A deep learning application to approximate the geometric orifice and coaptation areas of the polymeric heart valves under time - varying transvalvular pressure.

Journal of the mechanical behavior of biomedical materials
Machine learning and deep learning frameworks have been presented as a substitute for lengthy computational analysis, such as finite element analysis, computational fluid dynamics, and fluid-structure interaction. In this study, our objective was to ...

Automated Vision-Based Microsurgical Skill Analysis in Neurosurgery Using Deep Learning: Development and Preclinical Validation.

World neurosurgery
BACKGROUND/OBJECTIVE: Technical skill acquisition is an essential component of neurosurgical training. Educational theory suggests that optimal learning and improvement in performance depends on the provision of objective feedback. Therefore, the aim...

Functional annotation of human cognitive states using deep graph convolution.

NeuroImage
A key goal in neuroscience is to understand brain mechanisms of cognitive functions. An emerging approach is "brain decoding", which consists of inferring a set of experimental conditions performed by a participant, using pattern classification of br...

A deep learning model (ALNet) for the diagnosis of acute leukaemia lineage using peripheral blood cell images.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Morphological differentiation among blasts circulating in blood in acute leukaemia is challenging. Artificial intelligence decision support systems hold substantial promise as part of clinical practise in detecting haematol...

Predictive Analytics for Care and Management of Patients With Acute Diseases: Deep Learning-Based Method to Predict Crucial Complication Phenotypes.

Journal of medical Internet research
BACKGROUND: Acute diseases present severe complications that develop rapidly, exhibit distinct phenotypes, and have profound effects on patient outcomes. Predictive analytics can enhance physicians' care and management of patients with acute diseases...

GroupRegNet: a groupwise one-shot deep learning-based 4D image registration method.

Physics in medicine and biology
Accurate deformable four-dimensional (4D) (three-dimensional in space and time) medical images registration is essential in a variety of medical applications. Deep learning-based methods have recently gained popularity in this area for the significan...