AIMC Topic: Deep Learning

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Shading artifact correction in breast CT using an interleaved deep learning segmentation and maximum-likelihood polynomial fitting approach.

Medical physics
PURPOSE: The purpose of this work was twofold: (a) To provide a robust and accurate method for image segmentation of dedicated breast CT (bCT) volume data sets, and (b) to improve Hounsfield unit (HU) accuracy in bCT by means of a postprocessing meth...

A Literature Review: Geometric Methods and Their Applications in Human-Related Analysis.

Sensors (Basel, Switzerland)
Geometric features, such as the topological and manifold properties, are utilized to extract geometric properties. Geometric methods that exploit the applications of geometrics, e.g., geometric features, are widely used in computer graphics and compu...

Cell mitosis event analysis in phase contrast microscopy images using deep learning.

Medical image analysis
In this paper, we solve the problem of mitosis event localization and its stage localization in time-lapse phase-contrast microscopy images. Our method contains three steps: first, we formulate a Low-Rank Matrix Recovery (LRMR) model to find salient ...

Single-Particle Diffusion Characterization by Deep Learning.

Biophysical journal
Diffusion plays a crucial role in many biological processes including signaling, cellular organization, transport mechanisms, and more. Direct observation of molecular movement by single-particle-tracking experiments has contributed to a growing body...

3D-CNN based discrimination of schizophrenia using resting-state fMRI.

Artificial intelligence in medicine
MOTIVATION: This study reports a framework to discriminate patients with schizophrenia and normal healthy control subjects, based on magnetic resonance imaging (MRI) of the brain. Resting-state functional MRI data from a total of 144 subjects (72 pat...

Deep learning networks find unique mammographic differences in previous negative mammograms between interval and screen-detected cancers: a case-case study.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: To determine if mammographic features from deep learning networks can be applied in breast cancer to identify groups at interval invasive cancer risk due to masking beyond using traditional breast density measures.

Performance of a Deep-Learning Neural Network to Detect Intracranial Aneurysms from 3D TOF-MRA Compared to Human Readers.

Clinical neuroradiology
PURPOSE: To study the clinical potential of a deep learning neural network (convolutional neural networks [CNN]) as a supportive tool for detection of intracranial aneurysms from 3D time-of-flight magnetic resonance angiography (TOF-MRA) by comparing...

Automatic gas detection in prostate cancer patients during image-guided radiation therapy using a deep convolutional neural network.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: The detection of intestinal/rectal gas is very important during image-guided radiation therapy (IGRT) of prostate cancer patients because intestinal/rectal gas increases the inter- and intra-fractional prostate motion. We propose a deep conv...

A Deep Learning-Based Automatic Mosquito Sensing and Control System for Urban Mosquito Habitats.

Sensors (Basel, Switzerland)
Mosquito control is important as mosquitoes are extremely harmful pests that spread various infectious diseases. In this research, we present the preliminary results of an automated system that detects the presence of mosquitoes via image processing ...

Automated detection of third molars and mandibular nerve by deep learning.

Scientific reports
The approximity of the inferior alveolar nerve (IAN) to the roots of lower third molars (M3) is a risk factor for the occurrence of nerve damage and subsequent sensory disturbances of the lower lip and chin following the removal of third molars. To a...