AIMC Topic: Stomach

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Robot-assisted vs. laparoscopic repair of complete upside-down stomach hiatal hernia (the RATHER-study): a prospective comparative single center study.

Surgical endoscopy Feb 1, 2021
BACKGROUND: Complete upside-down stomach (cUDS) hernias are a subgroup of large hiatal hernias characterized by high risk of life-threatening complications and technically challenging surgical repair including complex mediastinal dissection. In a pro...
Laparoscopy Humans Stomach Recurrence Hernia, Hiatal Herniorrhaphy Prospective Studies Quality of Life Treatment Outcome Robotics
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Deep convolutional neural network-based anomaly detection for organ classification in gastric X-ray examination.

Computers in biology and medicine Jul 8, 2020
AIM: The aim of this study was to determine whether our deep convolutional neural network-based anomaly detection model can distinguish differences in esophagus images and stomach images obtained from gastric X-ray examinations.
Radiography Stomach X-Rays Humans Neural Networks, Computer
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SoGut: A Soft Robotic Gastric Simulator.

Soft robotics Jun 19, 2020
The human stomach breaks down and transports food by coordinated radial contractions of the gastric walls. The radial contractions periodically propagate through the stomach and constitute the peristaltic contractions, also called the gastric motilit...
Digestion Stomach Humans Manometry Robotics Peristalsis
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[Robot-Assisted Repeated Fundoplication in Children and Adolescents].

Zentralblatt fur Chirurgie Jun 18, 2020
BACKGROUND: Recurrent gastroesophageal reflux symptoms in adolescents and young adults who underwent fundoplication in childhood present a technical challenge for the surgeon. The distal oesophagus and hiatus are difficult to access by laparotomy, th...
Stomach Fundoplication Humans Adolescent Child, Preschool Child Treatment Outcome Robotics Laparoscopy Gastroesophageal Reflux
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Abdominal multi-organ auto-segmentation using 3D-patch-based deep convolutional neural network.

Scientific reports Apr 10, 2020
Segmentation of normal organs is a critical and time-consuming process in radiotherapy. Auto-segmentation of abdominal organs has been made possible by the advent of the convolutional neural network. We utilized the U-Net, a 3D-patch-based convolutio...
Algorithms Tomography, X-Ray Computed Female Aged Humans Neural Networks, Computer Liver Neoplasms Imaging, Three-Dimensional Kidney Duodenum Abdomen Aged, 80 and over Adult Male Middle Aged Liver Stomach
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A pilot trial of Convolution Neural Network for automatic retention-monitoring of capsule endoscopes in the stomach and duodenal bulb.

Scientific reports Mar 5, 2020
The retention of a capsule endoscope (CE) in the stomach and the duodenal bulb during the examination is a troublesome problem, which can make the medical staff spend several hours observing whether the CE enters the descending segment of the duodenu...
Aged, 80 and over Young Adult Adult Algorithms Sensitivity and Specificity Image Processing, Computer-Assisted Male Humans Stomach Retrospective Studies Duodenum Middle Aged Neural Networks, Computer Capsule Endoscopes Female Adolescent Automation Foreign Bodies Aged Monitoring, Intraoperative Capsule Endoscopy
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An objective comparison of detection and segmentation algorithms for artefacts in clinical endoscopy.

Scientific reports Feb 17, 2020
We present a comprehensive analysis of the submissions to the first edition of the Endoscopy Artefact Detection challenge (EAD). Using crowd-sourcing, this initiative is a step towards understanding the limitations of existing state-of-the-art comput...
Urinary Bladder International Cooperation Colon Imaging, Three-Dimensional Esophagus Uterus Image Interpretation, Computer-Assisted Artifacts Datasets as Topic Stomach Algorithms Female Endoscopy Male Humans Neural Networks, Computer
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Computational analysis of morphological and molecular features in gastric cancer tissues.

Cancer medicine Feb 3, 2020
Biological morphologies of cells and tissues represent their physiological and pathological conditions. The importance of quantitative assessment of morphological information has been highly recognized in clinical diagnosis and therapeutic strategies...
Machine Learning Repressor Proteins Stomach Neoplasms Tissue Array Analysis Humans Biomarkers, Tumor Image Processing, Computer-Assisted Immunohistochemistry B7-H1 Antigen Cell Membrane Feasibility Studies Stomach
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Engineering approaches for characterizing soft tissue mechanical properties: A review.

Clinical biomechanics (Bristol, Avon) Jul 16, 2019
From cancer diagnosis to detailed characterization of arterial wall biomechanics, the elastic property of tissues is widely studied as an early sign of disease onset. The fibrous structural features of tissues are a direct measure of its health and f...
Bioengineering Liver Area Under Curve Elasticity Imaging Techniques Diagnostic Imaging Microscopy, Atomic Force Tomography, Optical Coherence Biomechanical Phenomena Humans Elasticity Equipment Design Cell Membrane Male Machine Learning Robotic Surgical Procedures Vagina Neoplasms Female Prostate Stomach Fiber Optic Technology Brain Neoplasms Breast
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A Deep Learning Convolutional Neural Network Can Recognize Common Patterns of Injury in Gastric Pathology.

Archives of pathology & laboratory medicine Jun 27, 2019
CONTEXT.—: Most deep learning (DL) studies have focused on neoplastic pathology, with the realm of inflammatory pathology remaining largely untouched.
Helicobacter pylori Gastritis Diagnosis, Computer-Assisted Humans Stomach Deep Learning Neural Networks, Computer Stomach Diseases Biopsy Reproducibility of Results Helicobacter Infections Sensitivity and Specificity
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