AIMC Topic: Diagnostic Imaging
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Hierarchical medical image report adversarial generation with hybrid discriminator.
Artificial intelligence in medicine
Mar 21, 2024
BACKGROUND AND OBJECTIVES: Generating coherent reports from medical images is an important task for reducing doctors' workload. Unlike traditional image captioning tasks, the task of medical image report generation faces more challenges. Current mode...
Unlocking the Value: Quantifying the Return on Investment of Hospital Artificial Intelligence.
Journal of the American College of Radiology : JACR
Mar 16, 2024
PURPOSE: A comprehensive return on investment (ROI) calculator was developed to evaluate the monetary and nonmonetary benefits of an artificial intelligence (AI)-powered radiology diagnostic imaging platform to inform decision makers interested in ad...
Intelligent Integrated System for Fruit Detection Using Multi-UAV Imaging and Deep Learning.
Sensors (Basel, Switzerland)
Mar 16, 2024
In the context of Industry 4.0, one of the most significant challenges is enhancing efficiency in sectors like agriculture by using intelligent sensors and advanced computing. Specifically, the task of fruit detection and counting in orchards represe...
Checklist for Reproducibility of Deep Learning in Medical Imaging.
Journal of imaging informatics in medicine
Mar 14, 2024
The application of deep learning (DL) in medicine introduces transformative tools with the potential to enhance prognosis, diagnosis, and treatment planning. However, ensuring transparent documentation is essential for researchers to enhance reproduc...
Deep-learning approach to stratified reconstructions of tissue absorption and scattering in time-domain spatial frequency domain imaging.
Journal of biomedical optics
Mar 12, 2024
SIGNIFICANCE: The conventional optical properties (OPs) reconstruction in spatial frequency domain (SFD) imaging, like the lookup table (LUT) method, causes OPs aliasing and yields only average OPs without depth resolution. Integrating SFD imaging wi...
From CNN to Transformer: A Review of Medical Image Segmentation Models.
Journal of imaging informatics in medicine
Mar 4, 2024
Medical image segmentation is an important step in medical image analysis, especially as a crucial prerequisite for efficient disease diagnosis and treatment. The use of deep learning for image segmentation has become a prevalent trend. The widely ad...
Machine learning-based medical imaging diagnosis in patients with temporomandibular disorders: a diagnostic test accuracy systematic review and meta-analysis.
Clinical oral investigations
Mar 2, 2024
OBJECTIVES: Temporomandibular disorders (TMDs) are the second most common musculoskeletal condition which are challenging tasks for most clinicians. Recent research used machine learning (ML) algorithms to diagnose TMDs intelligently. This study aime...
Integrating AI in medicine: Lessons from Chat-GPT's limitations in medical imaging.
Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver
Feb 29, 2024
Empirical data drift detection experiments on real-world medical imaging data.
Nature communications
Feb 29, 2024
While it is common to monitor deployed clinical artificial intelligence (AI) models for performance degradation, it is less common for the input data to be monitored for data drift - systemic changes to input distributions. However, when real-time ev...
Deep neural networks can differentiate thyroid pathologies on infrared hyperspectral images.
Computer methods and programs in biomedicine
Feb 24, 2024
BACKGROUND AND OBJECTIVE: The thyroid is a gland responsible for producing important body hormones. Several pathologies can affect this gland, such as thyroiditis, hypothyroidism, and thyroid cancer. The visual histological analysis of thyroid specim...
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