Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
40040222
Robot-assisted surgical systems have shown promising results and better patient outcomes in pedicle screw instrumentation and percutaneous needle interventions. Many commercial robotic assistance systems are available for the aforementioned procedure...
Magnetic fields enable remote manipulation of objects and are ideal for medical applications because they pass through human tissue harmlessly. This capability is promising for surgical robots, allowing navigation deeper into the human anatomy and ac...
This study aims to explore the feasibility of a deep learning approach to correct the distortion caused by the skull, thereby developing a transcranial adaptive focusing method for safe ultrasonic treatment in opening of the blood-brain barrier (BBB)...
PURPOSE: Trityl OXO71-based pulse electron paramagnetic resonance imaging (EPRI) is an excellent technique to obtain partial pressure of oxygen (pO) maps in tissues. In this study, we used deep learning techniques to denoise 3D EPR amplitude and pO m...
Cancer imaging : the official publication of the International Cancer Imaging Society
40075547
PURPOSE: This study aimed to select robust features against lung motion in a phantom study and use them as input to feature selection algorithms and machine learning classifiers in a clinical study to predict the lymphovascular invasion (LVI) of non-...
The increasing use of ionizing radiation has raised concerns about adverse and long-term health risks for individuals. Therefore, to evaluate the range of risks and protection against ionizing radiation, it is necessary to assess the dosimetry calcul...
Adequate access to radiotherapy is a critical global concern affecting low-resource settings such as low- and middle-income countries and rural regions. We propose to reduce this disparity by developing a novel low-cost radiotherapy device that treat...
This work aims to develop and investigate the feasibility of a hybrid model combining Monte Carlo (MC) simulations and deep learning (DL) to predict electronic portal imaging device (EPID) images based on MC-generated exit phase space energy fluence ...
OBJECTIVE: To compare a deep learning (DL)-accelerated non-enhanced abbreviated MRI (AMRI) protocol with standard AMRI (AMRI) of the liver in terms of image quality and malignant focal lesion detection.
IEEE transactions on ultrasonics, ferroelectrics, and frequency control
40138245
Ultrasound computed tomography (USCT) is a promising technique for breast cancer detection because of its quantitative imaging capability of the speed of sound (SOS) of soft tissues and the fact that malignant breast lesions often have a higher SOS c...