AIMC Topic: Connective Tissue
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Anatomical recognition of dissection layers, nerves, vas deferens, and microvessels using artificial intelligence during transabdominal preperitoneal inguinal hernia repair.
Hernia : the journal of hernias and abdominal wall surgery
Dec 26, 2024
PURPOSE: In laparoscopic inguinal hernia surgery, proper recognition of loose connective tissue, nerves, vas deferens, and microvessels is important to prevent postoperative complications, such as recurrence, pain, sexual dysfunction, and bleeding. E...
The potential of AI-assisted gastrectomy with dual highlighting of pancreas and connective tissue.
Surgical oncology
Nov 22, 2024
BACKGROUND: Standard gastrectomy with D2 lymph node (LN) dissection for gastric cancer involves peripancreatic lymphadenectomy [1]. This technically demanding procedure requires meticulous dissection within the dissectable layers of connective tissue...
Automated segmentation by deep learning of loose connective tissue fibers to define safe dissection planes in robot-assisted gastrectomy.
Scientific reports
Oct 27, 2021
The prediction of anatomical structures within the surgical field by artificial intelligence (AI) is expected to support surgeons' experience and cognitive skills. We aimed to develop a deep-learning model to automatically segment loose connective ti...
Peak learning of mass spectrometry imaging data using artificial neural networks.
Nature communications
Sep 20, 2021
Mass spectrometry imaging (MSI) is an emerging technology that holds potential for improving, biomarker discovery, metabolomics research, pharmaceutical applications and clinical diagnosis. Despite many solutions being developed, the large data size ...
Histomorphological investigation of intrahepatic connective tissue for surgical anatomy based on modern computer imaging analysis.
Journal of hepato-biliary-pancreatic sciences
Jul 22, 2020
BACKGROUND/PURPOSE: Computer-assisted tissue imaging and analytical techniques were used to clarify the histomorphological structure of hepatic connective tissue as a practical guide for surgeons.
Automatic classification of IgA endomysial antibody test for celiac disease: a new method deploying machine learning.
Scientific reports
Jun 25, 2019
Widespread use of endomysial autoantibody (EmA) test in diagnostics of celiac disease is limited due to its subjectivity and its requirement of an expert evaluator. The study aimed to determine whether machine learning can be applied to create a new ...
Neural network modelling of soft tissue deformation for surgical simulation.
Artificial intelligence in medicine
Nov 13, 2018
This paper presents a new neural network methodology for modelling of soft tissue deformation for surgical simulation. The proposed methodology formulates soft tissue deformation and its dynamics as the neural propagation and dynamics of cellular neu...
Soft tissue deformation modelling through neural dynamics-based reaction-diffusion mechanics.
Medical & biological engineering & computing
May 30, 2018
Soft tissue deformation modelling forms the basis of development of surgical simulation, surgical planning and robotic-assisted minimally invasive surgery. This paper presents a new methodology for modelling of soft tissue deformation based on reacti...
Classification of cardiovascular tissues using LBP based descriptors and a cascade SVM.
Computer methods and programs in biomedicine
Jun 10, 2017
BACKGROUND AND OBJECTIVE: Histological images have characteristics, such as texture, shape, colour and spatial structure, that permit the differentiation of each fundamental tissue and organ. Texture is one of the most discriminative features. The au...
Epithelium-Stroma Classification via Convolutional Neural Networks and Unsupervised Domain Adaptation in Histopathological Images.
IEEE journal of biomedical and health informatics
Apr 6, 2017
Epithelium-stroma classification is a necessary preprocessing step in histopathological image analysis. Current deep learning based recognition methods for histology data require collection of large volumes of labeled data in order to train a new neu...
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