A5091761360- COVID-19 diagnosis using AI
- Lung Cancer Diagnosis and Treatment
- Radiomics and Machine Learning in Medical Imaging
- Medical Image Segmentation Techniques
- Infrared Thermography in Medicine
- Advanced MRI Techniques and Applications
- Ocular Diseases and Behçet’s Syndrome
- Advanced X-ray and CT Imaging
- Retinal and Optic Conditions
- Cerebral Venous Sinus Thrombosis
- Metabolomics and Mass Spectrometry Studies
- Radiology practices and education
- Neural Networks and Applications
- MRI in cancer diagnosis
- Cardiovascular Disease and Adiposity
- Ultrasound in Clinical Applications
- Functional Brain Connectivity Studies
- Thermal Regulation in Medicine
- Radiation Dose and Imaging
- Infectious Diseases and Tuberculosis
- Fuzzy Logic and Control Systems
National Institutes of Health Clinical Center
2022-2025
University of Iowa
2005
University of Iowa Hospitals and Clinics
1993-1994
Abstract Point-of-care ultrasound (POCUS) has emerged as a standard of care across variety healthcare settings due to its ability provide critical clinical information and well procedural guidance clinicians directly at the bedside. Implementation enterprise imaging (EI) strategies is needed such that POCUS images can be appropriately captured, indexed, managed, stored, distributed, viewed, analyzed. Because unique workflow educational requirements, reliance on traditional order-based...
Automatic detection of some pulmonary abnormalities using chest X-rays may be impacted adversely due to obscuring by bony structures like the ribs and clavicles. Automated bone suppression methods would increase soft tissue visibility enhance automated disease detection. We evaluate this hypothesis a custom ensemble convolutional neural network models, which we call DeBoNet, that suppresses bones in frontal CXRs. First, train variants U-Nets, Feature Pyramid Networks, other proposed models...
The segmentation of the image is a useful opera- tion in several medical processing tasks. Two examples are extraction lung tissue from x-ray and segregation gray matter, white cerebrospinal fluid brain images. Since needs of- ten related to anatomy object, most naturally done anatomical images like x-ray, Comput- erized Tomography (CT), or Magnetic Resonance (MR) An advantage use MR-images that they can be acquired as multicomponent therefore pixelwise based on more information than images,...