AIMC Topic: Tomography

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Machine Learning-Based Identification of Risk Factors of Keratoconus Progression Using Raw Corneal Tomography Data.

Cornea Aug 20, 2024
PURPOSE: The purpose of this study was to identify early indicators of keratoconus progression in Pentacam data using machine learning (ML) techniques.
Cornea Male Middle Aged Young Adult Adult Keratoconus Corneal Topography Tomography Disease Progression Adolescent ROC Curve Humans Machine Learning Retrospective Studies Female Risk Factors
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UroAngel: a single-kidney function prediction system based on computed tomography urography using deep learning.

World journal of urology Apr 16, 2024
BACKGROUND: Accurate estimation of the glomerular filtration rate (GFR) is clinically crucial for determining the status of obstruction, developing treatment strategies, and predicting prognosis in obstructive nephropathy (ON). We aimed to develop a ...
Retrospective Studies Deep Learning Kidney Humans Renal Insufficiency, Chronic Glomerular Filtration Rate Creatinine Tomography Solitary Kidney
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Predicting malnutrition in gastric cancer patients using computed tomography(CT) deep learning features and clinical data.

Clinical nutrition (Edinburgh, Scotland) Feb 6, 2024
OBJECTIVE: The aim of this study is using clinical factors and non-enhanced computed tomography (CT) deep features of the psoas muscles at third lumbar vertebral (L3) level to construct a model to predict malnutrition in gastric cancer before surgery...
Malnutrition Albumins Phenylenediamines Stomach Neoplasms Deep Learning Benzamides Tomography Humans Retrospective Studies
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Ultrasound tomography enhancement by signal feature extraction with modular machine learning method.

PloS one Jan 31, 2024
Robust and reliable diagnostic methods are desired in various types of industries. This article presents a novel approach to object detection in industrial or general ultrasound tomography. The key idea is to analyze the time-dependent ultrasonic sig...
Machine Learning Ultrasonography Tomography Neural Networks, Computer
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Model-based deep learning framework for accelerated optical projection tomography.

Scientific reports Dec 8, 2023
In this work, we propose a model-based deep learning reconstruction algorithm for optical projection tomography (ToMoDL), to greatly reduce acquisition and reconstruction times. The proposed method iterates over a data consistency step and an image d...
Phantoms, Imaging Tomography Image Processing, Computer-Assisted Zebrafish Neural Networks, Computer Algorithms Animals Deep Learning
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Deep learning model for measuring the sagittal Cobb angle on cervical spine computed tomography.

BMC medical imaging Nov 28, 2023
PURPOSES: To develop a deep learning (DL) model to measure the sagittal Cobb angle of the cervical spine on computed tomography (CT).
Spine Tomography Tomography, X-Ray Computed Humans Deep Learning Cervical Vertebrae
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Noninvasive Computed Tomography-Based Deep Learning Model Predicts In Vitro Chemosensitivity Assay Results in Pancreatic Cancer.

Pancreas Nov 24, 2023
OBJECTIVES: We aimed to predict in vitro chemosensitivity assay results from computed tomography (CT) images by applying deep learning (DL) to optimize chemotherapy for pancreatic ductal adenocarcinoma (PDAC).
Fluorouracil Carcinoma, Pancreatic Ductal Paclitaxel Drug Resistance, Neoplasm Deep Learning Gemcitabine Pancreatic Neoplasms Tomography Drug Screening Assays, Antitumor Humans
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Aortic Annulus Detection Based on Deep Learning for Transcatheter Aortic Valve Replacement Using Cardiac Computed Tomography.

Journal of Korean medical science Sep 18, 2023
BACKGROUND: To propose a deep learning architecture for automatically detecting the complex structure of the aortic annulus plane using cardiac computed tomography (CT) for transcatheter aortic valve replacement (TAVR).
Tomography Deep Learning Humans Radiography Retrospective Studies Transcatheter Aortic Valve Replacement
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A Deep Learning Image Reconstruction Algorithm for Improving Image Quality and Hepatic Lesion Detectability in Abdominal Dual-Energy Computed Tomography: Preliminary Results.

Journal of digital imaging Aug 14, 2023
This study aimed to compare the performance of deep learning image reconstruction (DLIR) and adaptive statistical iterative reconstruction-Veo (ASIR-V) in improving image quality and diagnostic performance using virtual monochromatic spectral images ...
Abdomen Radiographic Image Interpretation, Computer-Assisted Radiation Dosage Deep Learning Image Processing, Computer-Assisted Tomography Humans Algorithms Male
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A deep-learning assisted bioluminescence tomography method to enable radiation targeting in rat glioblastoma.

Physics in medicine and biology Jul 24, 2023
. A novel solution is required for accurate 3D bioluminescence tomography (BLT) based glioblastoma (GBM) targeting. The provided solution should be computationally efficient to support real-time treatment planning, thus reducing the x-ray imaging dos...
Cone-Beam Computed Tomography Models, Animal Animals Tomography Rats Deep Learning Glioblastoma
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