AIMC Topic: Deep Learning

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Cone Beam CT (CBCT) Based Synthetic CT Generation Using Deep Learning Methods for Dose Calculation of Nasopharyngeal Carcinoma Radiotherapy.

Technology in cancer research & treatment
To generate synthetic CT (sCT) images with high quality from CBCT and planning CT (pCT) for dose calculation by using deep learning methods. 169 NPC patients with a total of 20926 slices of CBCT and pCT images were included. In this study the Cycle...

[Effect of Automatic Extraction Accuracy by Different Image Reconstruction Methods Using a Three-dimensional Image Analysis System for Pulmonary Segmentectomy Preoperative CT Angiography].

Nihon Hoshasen Gijutsu Gakkai zasshi
This study aimed to determine the optimal image reconstruction method for preoperative computed tomography (CT) angiography for pulmonary segmentectomy. This study enrolled 20 patients who underwent contrast-enhanced CT examination for pulmonary segm...

Prediction and comparison of postural discomfort based on MLP and quadratic regression.

Journal of occupational health
OBJECTIVE: The objective of this study was to predict postural discomfort based on the deep learning-based regression (multilayer perceptron [MLP] model).

[Forefront of AI Applications for COVID-19 Imaging Diagnosis].

Igaku butsuri : Nihon Igaku Butsuri Gakkai kikanshi = Japanese journal of medical physics : an official journal of Japan Society of Medical Physics
The intra- and inter-observer variability in diagnosis of thoracic CT images may affect the diagnosis of COVID-19. Therefore, several studies have been reported to develop artificial intelligence (AI) approaches using deep learning (DL) and radiomics...

An Optimized Decision Tree with Genetic Algorithm Rule-Based Approach to Reveal the Brain's Changes During Alzheimer's Disease Dementia.

Journal of Alzheimer's disease : JAD
BACKGROUND: It is desirable to achieve acceptable accuracy for computer aided diagnosis system (CADS) to disclose the dementia-related consequences on the brain. Therefore, assessing and measuring these impacts is fundamental in the diagnosis of deme...

[Automatic Quantification of Breast Density from Mammography Using Deep Learning].

Nihon Hoshasen Gijutsu Gakkai zasshi
BACKGROUND: In the field of breast screening using mammography, announcing to the examinees whether they are dense or not has not been deprecated in Japan. One of the reasons is a shortage of objectivity estimating their dense breast. Our aim is to b...

[Automation of Damage Detection and Damage Area Measurement of X-ray Protective Clothing Using Deep Learning].

Nihon Hoshasen Gijutsu Gakkai zasshi
PURPOSE: Damage to shielding sheets on X-ray protective clothing may be a cause of increased radiation exposure. To prevent increased radiation exposure, periodic quality control of shielding sheets is needed. For quality management, a record of the ...

Monte Carlo Dose Calculation Using MRI Based Synthetic CT Generated by Fully Convolutional Neural Network for Gamma Knife Radiosurgery.

Technology in cancer research & treatment
The aim of this work is to study the dosimetric effect from generated synthetic computed tomography (sCT) from magnetic resonance (MR) images using a deep learning algorithm for Gamma Knife (GK) stereotactic radiosurgery (SRS). The Monte Carlo (MC) m...

Impact of novel deep learning image reconstruction algorithm on diagnosis of contrast-enhanced liver computed tomography imaging: Comparing to adaptive statistical iterative reconstruction algorithm.

Journal of X-ray science and technology
OBJECTIVE: To assess clinical application of applying deep learning image reconstruction (DLIR) algorithm to contrast-enhanced portal venous phase liver computed tomography (CT) for improving image quality and lesions detection rate compared with usi...

Analysis of segmentation of lung parenchyma based on deep learning methods.

Journal of X-ray science and technology
Precise segmentation of lung parenchyma is essential for effective analysis of the lung. Due to the obvious contrast and large regional area compared to other tissues in the chest, lung tissue is less difficult to segment. Special attention to detail...