AIMC Topic: Image Processing, Computer-Assisted

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Artificial intelligence (A.I.) in dental curricula: Ethics and responsible integration.

Journal of dental education
The use of artificial intelligence (AI) is deeply embedded in all aspects of our daily lives, promoting efficiency and safety in routine tasks at home and work. Likewise, dentistry is rapidly exploring new uses of AI for image analysis, electronic he...

Highly Flexible Deep-Learning-Based Automatic Analysis for Graphically Encoded Hydrogel Microparticles.

ACS sensors
Graphically encoded hydrogel microparticle (HMP)-based bioassay is a diagnostic tool characterized by exceptional multiplex detectability and robust sensitivity and specificity. Specifically, deep learning enables highly fast and accurate analyses of...

Application of Semi-supervised Fuzzy Clustering Based on Knowledge Weighting and Cluster Center Learning to Mammary Molybdenum Target Image Segmentation.

Interdisciplinary sciences, computational life sciences
Breast cancer is commonly diagnosed with mammography. Using image segmentation algorithms to separate lesion areas in mammography can facilitate diagnosis by doctors and reduce their workload, which has important clinical significance. Because large,...

ROOD-MRI: Benchmarking the robustness of deep learning segmentation models to out-of-distribution and corrupted data in MRI.

NeuroImage
Deep artificial neural networks (DNNs) have moved to the forefront of medical image analysis due to their success in classification, segmentation, and detection challenges. A principal challenge in large-scale deployment of DNNs in neuroimage analysi...

Recent progress in transformer-based medical image analysis.

Computers in biology and medicine
The transformer is primarily used in the field of natural language processing. Recently, it has been adopted and shows promise in the computer vision (CV) field. Medical image analysis (MIA), as a critical branch of CV, also greatly benefits from thi...

Standardized motion detection and real time heart rate monitoring of aerobics training based on convolution neural network.

Preventive medicine
In order to make the teaching and training of aerobics more standardized, it is necessary to use scientific means to detect and monitor the movement standardization in teaching and training and the change of human heart rate in the training process, ...

Imaging inside highly scattering media using hybrid deep learning and analytical algorithm.

Journal of biophotonics
Imaging through highly scattering media is a challenging problem with numerous applications in biomedical and remote-sensing fields. Existing methods that use analytical or deep learning tools are limited by simplified forward models or a requirement...

Exploring contrast generalisation in deep learning-based brain MRI-to-CT synthesis.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
BACKGROUND: Synthetic computed tomography (sCT) has been proposed and increasingly clinically adopted to enable magnetic resonance imaging (MRI)-based radiotherapy. Deep learning (DL) has recently demonstrated the ability to generate accurate sCT fro...

Deep-Learning-Enabled Microwave-Induced Thermoacoustic Tomography Based on ResAttU-Net for Transcranial Brain Hemorrhage Detection.

IEEE transactions on bio-medical engineering
OBJECTIVE: Hemorrhagic stroke is a leading threat to human's health. The fast-developing microwave-induced thermoacoustic tomography (MITAT) technique holds potential to do brain imaging. However, transcranial brain imaging based on MITAT is still ch...

P-TransUNet: an improved parallel network for medical image segmentation.

BMC bioinformatics
Deep learning-based medical image segmentation has made great progress over the past decades. Scholars have proposed many novel transformer-based segmentation networks to solve the problems of building long-range dependencies and global context conne...