AIMC Topic: Diagnostic Imaging
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MLP-Like Model With Convolution Complex Transformation for Auxiliary Diagnosis Through Medical Images.
IEEE journal of biomedical and health informatics
Sep 6, 2023
Medical images such as facial and tongue images have been widely used for intelligence-assisted diagnosis, which can be regarded as the multi-label classification task for disease location (DL) and disease nature (DN) of biomedical images. Compared w...
Semantic-Aware Contrastive Learning for Multi-Object Medical Image Segmentation.
IEEE journal of biomedical and health informatics
Sep 6, 2023
Medical image segmentation, or computing voxel-wise semantic masks, is a fundamental yet challenging task in medical imaging domain. To increase the ability of encoder-decoder neural networks to perform this task across large clinical cohorts, contra...
Implementing AI in breast imaging: challenges to turn the gadget into gain.
European radiology
Sep 4, 2023
Deep learning-based detection and quantification of brain metastases on black-blood imaging can provide treatment suggestions: a clinical cohort study.
European radiology
Sep 2, 2023
OBJECTIVES: We aimed to evaluate whether deep learning-based detection and quantification of brain metastasis (BM) may suggest treatment options for patients with BMs.
A scoping review on multimodal deep learning in biomedical images and texts.
Journal of biomedical informatics
Aug 29, 2023
OBJECTIVE: Computer-assisted diagnostic and prognostic systems of the future should be capable of simultaneously processing multimodal data. Multimodal deep learning (MDL), which involves the integration of multiple sources of data, such as images an...
New trend in artificial intelligence-based assistive technology for thoracic imaging.
La Radiologia medica
Aug 28, 2023
Although there is no solid agreement for artificial intelligence (AI), it refers to a computer system with intelligence similar to that of humans. Deep learning appeared in 2006, and more than 10 years have passed since the third AI boom was triggere...
DEBI-NN: Distance-encoding biomorphic-informational neural networks for minimizing the number of trainable parameters.
Neural networks : the official journal of the International Neural Network Society
Aug 25, 2023
Modern artificial intelligence (AI) approaches mainly rely on neural network (NN) or deep NN methodologies. However, these approaches require large amounts of data to train, given, that the number of their trainable parameters has a polynomial relati...
Deep learning analysis of mid-infrared microscopic imaging data for the diagnosis and classification of human lymphomas.
Journal of biophotonics
Aug 23, 2023
The present study presents an alternative analytical workflow that combines mid-infrared (MIR) microscopic imaging and deep learning to diagnose human lymphoma and differentiate between small and large cell lymphoma. We could show that using a deep l...
An overview of ultrasound-derived radiomics and deep learning in liver.
Medical ultrasonography
Aug 22, 2023
Over the past few years, developments in artificial intelligence (AI), especially in radiomics and deep learning, have enabled the extraction of pathophysiology-related information from varied medical imaging and are progressively transforming medica...
Feature-aware unsupervised lesion segmentation for brain tumor images using fast data density functional transform.
Scientific reports
Aug 21, 2023
We demonstrate that isomorphically mapping gray-level medical image matrices onto energy spaces underlying the framework of fast data density functional transform (fDDFT) can achieve the unsupervised recognition of lesion morphology. By introducing t...
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