Vision loss due to illness can result from various medical conditions that affect the eyes. Advanced devices like OCT and ultra-widefield retinal cameras are expensive, making them less accessible in resource-limited settings. While eye image capture...
The increasing use of manipulated videos has raised serious concerns in digital security and media authenticity. Deepfakes are particularly challenging to detect due to their realistic facial movements and seamless frame transitions. To overcome the ...
Breast cancer detection and diagnosis remain challenging due to the complexity of tumor tissues and image quality variations, which hinder early and accurate identification. Timely diagnosis is vital for initiating treatment and improving patient out...
The nnU-Net framework has played a crucial role in medical image segmentation and has become the gold standard in multitudes of applications targeting different diseases, organs, and modalities. However, so far it has been used primarily in a central...
Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Nov 3, 2025
Metastatic castration-resistant prostate cancer has a high rate of mortality with a limited number of effective treatments after hormone therapy. Radiopharmaceutical therapy with [Lu]Lu-prostate-specific membrane antigen-617 (LuPSMA) is one treatment...
Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Nov 3, 2025
Combined PET/CT imaging provides critical insights into both anatomic and molecular processes, yet traditional single-tracer approaches limit multidimensional disease phenotyping; to address this, we developed the PET Unified Multitracer Alignment (P...
Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Nov 3, 2025
We developed and evaluated an artificial intelligence (AI)-powered approach for easier quantification of tau PET uptake without requiring structural MR to aid earlier tracking of Alzheimer disease (AD). We implemented a deep neural network model tha...
In modern precision agriculture, early and accurate identification of crop diseases is crucial for reducing yield loss and minimizing pesticide overuse. This study proposes an IoT-enabled framework that integrates convolutional neural networks (CNNs)...
Automated brain tumor detection represents a fundamental challenge in contemporary medical imaging, demanding both precision and computational feasibility for practical implementation. This research introduces a novel Vision Transformer (ViT) framewo...
Colorectal cancer remains a leading cause of cancer-related mortality worldwide, emphasizing the importance of early detection through accurate polyp identification. However, colonoscopy relies heavily on precise polyp segmentation in endoscopic imag...
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