AIMC Topic: Image Processing, Computer-Assisted

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A Comparative Evaluation of Microimpedance Tomography Reconstruction Algorithms for in Vitro Imaging.

ACS sensors
This paper presents the development of a novel miniature electrical impedance tomography (EIT) system made out of glass, along with the training, validation, and testing of an accompanying open-source machine learning image reconstruction model. Our ...

Long-range correlation-guided dual-encoder fusion network for medical images.

Scientific reports
Multimodal medical image fusion plays an important role in clinical applications. However, multimodal medical image fusion methods ignore the feature dependence among modals, and the feature fusion ability with different granularity is not strong. A ...

An improved facial emotion recognition system using convolutional neural network for the optimization of human robot interaction.

Scientific reports
Artificial intelligence (AI) has been effectively augmenting the features of robotics applications, including surveillance, medical support, aid services for the elderly or disabled, and many more uses. Most robotics applications need a variety of hu...

Transformer-based multiclass segmentation pipeline for basic kidney histology.

Scientific reports
Current applications of deep learning in renal pathology focused on anatomical structures with morphology, yet little research has focused on the performance of models, such as versatility, in regions with severe kidney damage. In this study, we expl...

A multi-scale attention-based Swin transformer model for medical images segmentation.

Scientific reports
Medical image segmentation is crucial in accurately diagnosing diseases and assisting physicians in examining relevant areas. Therefore, there is a pressing need for an artificial intelligence-based model that can facilitate the diagnostic process an...

Automatic detection of sister chromatid exchanges using machine learning models and image analysis algorithms.

Scientific reports
After DNA replication, two chromatids with identical genetic information are formed in organisms; these are called sister chromatids. Sister chromatid exchange (SCE) is a recombination event between genetically equivalent sequences. Since no genetic ...

Improve deep learning-based reconstruction of optical coherence tomography angiography by siamese U-Net.

Biomedical physics & engineering express
Optical coherence tomography angiography (OCTA), as a functional imaging based on OCT, has found successful medical applications. OCTA produces vasculature imaging using blood flow motion as an intrinsic contrast agent. To date, the prevailing OCTA a...

Torso synthetic CT generation by integrating deep learning and segmentation for FDG-PET/MR attenuation correction.

Biomedical physics & engineering express
Positron Emission Tomography/Magnetic Resonance () offers benefits over PET/CT including simultaneous PET and MR acquisition, intrinsic spatial registration accuracy, MR-based functional information, and superior soft tissue contrast. However, accura...

CSCST-Net: a fully sparse-regularized convolutional sparse coding network for low-dose CT denoising.

Biomedical physics & engineering express
. Most low-dose computed tomography (LDCT) denoising methods based on CNN have some denoising effect, but their interpretability is very low due to the black-box nature of neural networks.. To address this issue, we propose a novel fully sparse-regul...

Broad-spectrum eye disease classification using a deep learning-based tailored software lens.

PloS one
The early and accurate classification of eye diseases is essential for preventing irreversible visual impairment. This task can be performed by deep learning approaches that automatically classify retinal fundus images according to potential illnesse...