AI Medical Compendium Journal:
Nihon Hoshasen Gijutsu Gakkai zasshi

Showing 41 to 50 of 54 articles

[Application of Convolutional Neural Network for Evaluating CT Dose Using Image Noise Classification: A Phantom Study].

Nihon Hoshasen Gijutsu Gakkai zasshi
PURPOSE: It is well known that there is a trade-off relationship between image noise and exposure dose in X-ray computed tomography (CT) examination. Therefore, CT dose level was evaluated by using the CT image noise property. Although noise power sp...

[Volume Measurements of Post-transplanted Liver of Pediatric Recipients Using Workstations and Deep Learning].

Nihon Hoshasen Gijutsu Gakkai zasshi
PURPOSE: The purpose of this study was to propose a method for segmentation and volume measurement of graft liver and spleen of pediatric transplant recipients on digital imaging and communications in medicine (DICOM) -format images using U-Net and t...

[Supplementing a Web-based Exposure Estimation System with Deep Learning for Automatic Classification of CT Images to Increase the Efficiency of Effective Dose Estimation].

Nihon Hoshasen Gijutsu Gakkai zasshi
PURPOSE: Web-based exposure estimation systems are advantageous for estimating exposure doses for computed tomography (CT) scans. However, such systems depend on the imaging conditions of the slices, and a considerable amount of time and effort is ne...

[Development of CT Pelvimetry Using Deep Learning Based Reconstruction].

Nihon Hoshasen Gijutsu Gakkai zasshi
PURPOSE: X-ray pelvimetry is typically performed for the diagnosis of the cephalopelvic disproportion (CPD). The purpose of this study was to assess the utility of new computed tomography (CT) reconstruction "deep learning based reconstruction (DLR) ...

[Impact of DVH Outliers Registered in Knowledge-based Planning on Volumetric Modulated Arc Therapy Treatment Planning for Prostate Cancer].

Nihon Hoshasen Gijutsu Gakkai zasshi
RapidPlan, a knowledge-based planning software, uses a model library containing the dose-volume histogram (DVH) of previous treatment plans, and it automatically provides optimization objectives based on a trained model to future patients for volumet...

[Automated Classification of Calcification and Stent on Computed Tomography Coronary Angiography Using Deep Learning].

Nihon Hoshasen Gijutsu Gakkai zasshi
In computed tomography coronary angiography (CTCA), calcification and stent make it difficult to evaluate intravascular lumen. This is a cause of low positive-predictive value of coronary stenosis. Therefore, it is expected to develop a computer-aide...