AI Medical Compendium Journal:
Biomedical physics & engineering express

Showing 81 to 90 of 142 articles

CRPU-NET: a deep learning model based semantic segmentation for the detection of colorectal polyp in lower gastrointestinal tract.

Biomedical physics & engineering express
. The objectives of the proposed work are twofold. Firstly, to develop a specialized light weight CRPU-Net for the segmentation of polyps in colonoscopy images. Secondly, to conduct a comparative analysis of the performance of CRPU-Net with implement...

Secret learning for lung cancer diagnosis-a study with homomorphic encryption, texture analysis and deep learning.

Biomedical physics & engineering express
Advanced lung cancer diagnoses from radiographic images include automated detection of lung cancer from CT-Scan images of the lungs. Deep learning is a popular method for decision making which can be used to classify cancerous and non-cancerous lungs...

Use of deep learning to segment bolus during videofluoroscopic swallow studies.

Biomedical physics & engineering express
Anatomical segmentations generated using artificial intelligence (AI) have the potential to significantly improve video fluoroscopic swallow study (VFS) analysis. AI segments allow for various metrics to be determined without additional time constrai...

Estimating blurless and noise-free Ir-192 source images from gamma camera images for high-dose-rate brachytherapy using a deep-learning approach.

Biomedical physics & engineering express
. Precise monitoring of the position and dwell time of iridium-192 (Ir-192) during high-dose-rate (HDR) brachytherapy is crucial to avoid serious damage to normal tissues. Source imaging using a compact gamma camera is a potential approach for monito...

Comparison of post reconstruction- and reconstruction-based deep learning denoising methods in cardiac SPECT.

Biomedical physics & engineering express
. The quality of myocardial perfusion SPECT (MPS) images is often hampered by low count statistics. Poor image quality might hinder reporting the studies and in the worst case lead to erroneous diagnosis. Deep learning (DL)-based methods can be used ...

Deep-learning-based image segmentation for image-based computational hemodynamic analysis of abdominal aortic aneurysms: a comparison study.

Biomedical physics & engineering express
Computational hemodynamics is increasingly being used to quantify hemodynamic characteristics in and around abdominal aortic aneurysms (AAA) in a patient-specific fashion. However, the time-consuming manual annotation hinders the clinical translation...

Generation of synthetic CT from CBCT using deep learning approaches for head and neck cancer patients.

Biomedical physics & engineering express
To create a synthetic CT (sCT) from daily CBCT using either deep residual U-Net (DRUnet), or conditional generative adversarial network (cGAN) for adaptive radiotherapy planning (ART).First fraction CBCT and planning CT (pCT) were collected from 93 H...

Classification of electrocardiogram signals using deep learning based on genetic algorithm feature extraction.

Biomedical physics & engineering express
Arrhythmias using electrocardiogram (ECG) signal is important in medical and computer research due to the timely diagnosis of dangerous cardiac conditions. The current study used the ECG to classify cardiac signals into normal heartbeats, congestive ...

A computationally-inexpensive strategy in CT image data augmentation for robust deep learning classification in the early stages of an outbreak.

Biomedical physics & engineering express
Coronavirus disease 2019 (COVID-19) has spread globally for over three years, and chest computed tomography (CT) has been used to diagnose COVID-19 and identify lung damage in COVID-19 patients. Given its widespread, CT will remain a common diagnosti...

EEG motor imagery classification using deep learning approaches in naïve BCI users.

Biomedical physics & engineering express
Motor Imagery (MI)-Brain Computer-Interfaces (BCI) illiteracy defines that not all subjects can achieve a good performance in MI-BCI systems due to different factors related to the fatigue, substance consumption, concentration, and experience in the ...