PURPOSE: This study aims to compare the effects of two types of deep learning (DL) techniques on brain CT values, image noise content, and contrast-to-noise ratio (CNR) between white and gray matter in low-noise head CT images, along with adaptive it...
IEEE journal of translational engineering in health and medicine
40035027
The high volume of emergency room patients often necessitates head CT examinations to rule out ischemic, hemorrhagic, or other organic pathologies. A system that enhances the diagnostic efficacy of head CT imaging in emergency settings through struct...
International journal of computer assisted radiology and surgery
39777700
PURPOSE: Systems equipped with natural language (NLP) processing can reduce missed radiological findings by physicians, but the annotation costs are burden in the development. This study aimed to compare the effects of active learning (AL) algorithms...
Therapeutic protocols involving subretinal injection, which hold the promise of saving or restoring sight, are challenging for surgeons because they are at the limits of human motor and perceptual abilities. Excessive or insufficient indentation of t...
Key challenges in upper limb prosthetics include a lack of effective control systems, the often invasive surgical requirements of brain-controlled limbs, and prohibitive costs. As a result, disuse rates remain high despite potential for increased qua...
Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine
40112700
PURPOSE: This study aims to investigate estimation of patient-specific organ doses from CT scans via radiomics feature-based SVR models with training parameter optimization, and maximize SVR models' predictive accuracy and robustness via fine-tuning ...
The head-related transfer function (HRTF) characterizes the frequency response of the sound traveling path between a specific location and the ear. When it comes to estimating HRTFs by neural network models, angle-specific models greatly outperform g...
Computational uncertainty and variability of power absorption and temperature rise in humans for radiofrequency (RF) exposure is a critical factor in ensuring human protection. This aspect has been emphasized as a priority. However, accurately modeli...
OBJECTIVE: Compare the image quality of image reconstructed using deep learning-based image reconstruction (DLIR) and iterative reconstruction algorithms for head and neck dual-energy CT angiography (DECTA).
We created and validated an open-access AI algorithm (AIc) for assessing image segmentation and patient centering in a multi-body-region, multi-center, and multi-scanner study. Our study included 825 head, chest, and abdomen-pelvis CT from 275 patien...