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Intestines

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Performance of convolutional neural networks for identification of bacteria in 3D microscopy datasets.

PLoS computational biology
Three-dimensional microscopy is increasingly prevalent in biology due to the development of techniques such as multiphoton, spinning disk confocal, and light sheet fluorescence microscopies. These methods enable unprecedented studies of life at the m...

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...

OrgaQuant: Human Intestinal Organoid Localization and Quantification Using Deep Convolutional Neural Networks.

Scientific reports
Organoid cultures are proving to be powerful in vitro models that closely mimic the cellular constituents of their native tissue. Organoids are typically expanded and cultured in a 3D environment using either naturally derived or synthetic extracellu...

Robotic fluidic coupling and interrogation of multiple vascularized organ chips.

Nature biomedical engineering
Organ chips can recapitulate organ-level (patho)physiology, yet pharmacokinetic and pharmacodynamic analyses require multi-organ systems linked by vascular perfusion. Here, we describe an 'interrogator' that employs liquid-handling robotics, custom s...

In Silico Prediction of Intestinal Permeability by Hierarchical Support Vector Regression.

International journal of molecular sciences
The vast majority of marketed drugs are orally administrated. As such, drug absorption is one of the important drug metabolism and pharmacokinetics parameters that should be assessed in the process of drug discovery and development. A nonlinear quant...

Automatic segmentation of pelvic organs-at-risk using a fusion network model based on limited training samples.

Acta oncologica (Stockholm, Sweden)
Efficient and accurate methods are needed to automatically segmenting organs-at-risk (OAR) to accelerate the radiotherapy workflow and decrease the treatment wait time. We developed and evaluated the use of a fused model Dense V-Network for its abil...

Pseudo-pneumatosis of the gastrointestinal tract: its incidence and the accuracy of a checklist supported by artificial intelligence (AI) techniques to reduce the misinterpretation of pneumatosis.

Emergency radiology
PURPOSE: To assess the incidence of erroneous diagnosis of pneumatosis (pseudo-pneumatosis) in patients who underwent an emergency abdominal CT and to verify the performance of imaging features, supported by artificial intelligence (AI) techniques, t...

Simultaneous Recognition of Atrophic Gastritis and Intestinal Metaplasia on White Light Endoscopic Images Based on Convolutional Neural Networks: A Multicenter Study.

Clinical and translational gastroenterology
INTRODUCTION: Patients with atrophic gastritis (AG) or gastric intestinal metaplasia (GIM) have elevated risk of gastric adenocarcinoma. Endoscopic screening and surveillance have been implemented in high incidence countries. The study aimed to evalu...

Design and implementation of a highly integrated dual hemisphere capsule robot.

Biomedical microdevices
To achieve cancer screening in any appointed position in 3D regions of the gastrointestinal (GI) tract such as esophagus, stomach and colon, a highly integrated dual hemisphere capsule robot (DHCR) with a novel three-layer nested structure is propose...