Journal of nuclear medicine technology
Dec 4, 2024
Generative artificial intelligence (AI) text-to-image production could reinforce or amplify gender and ethnicity biases. Several text-to-image generative AI tools are used for producing images that represent the medical imaging professions. White mal...
Skin melanin lesions are typically identified as tiny patches on the skin, which are impacted by melanocyte cell overgrowth. The number of people with skin cancer is increasing worldwide. Accurate and timely skin cancer identification is critical to ...
Neural networks : the official journal of the International Neural Network Society
Dec 3, 2024
Few-shot image generation aims at generating novel images for the unseen category when given K images from the same category. Despite significant advancements in existing few-shot image generation methods, great challenges remain regarding the qualit...
BACKGROUND: Cone-beam computed tomography (CBCT) is a crucial daily imaging modality in image-guided and adaptive radiotherapy. However, the use of ionizing radiation in CBCT imaging increases the risk of secondary cancers, which is particularly conc...
This study systematically reviews CNN-based medical image classification methods. We surveyed 149 of the latest and most important papers published to date and conducted an in-depth analysis of the methods used therein. Based on the selected literatu...
Journal of applied clinical medical physics
Dec 3, 2024
BACKGROUND: Four-dimensional CT is increasingly used for functional cardiac imaging, including prognosis for conditions such as heart failure and post myocardial infarction. However, radiation dose from an acquisition spanning the full cardiac cycle ...
Early detection of colorectal carcinoma (CRC), one of the most prevalent forms of cancer worldwide, significantly enhances the prognosis of patients. This research presents a new method for improving CRC detection using a deep learning ensemble with ...
The latest developments combining deep learning technology and medical image data have attracted wide attention and provide efficient noninvasive methods for the early diagnosis of breast cancer. The success of this task often depends on a large amou...
The utilization of artificial intelligence (AI) is expanding significantly within medical research and, to some extent, in clinical practice. Deep learning (DL) applications, which use large convolutional neural networks (CNN), hold considerable pote...
In modern medical imaging-assisted therapies, manual annotation is commonly employed for liver and tumor segmentation in abdominal CT images. However, this approach suffers from low efficiency and poor accuracy. With the development of deep learning,...
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