AIMC Topic: Image Processing, Computer-Assisted

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LinFlo-Net: A Two-Stage Deep Learning Method to Generate Simulation Ready Meshes of the Heart.

Journal of biomechanical engineering
We present a deep learning model to automatically generate computer models of the human heart from patient imaging data with an emphasis on its capability to generate thin-walled cardiac structures. Our method works by deforming a template mesh to fi...

[Research of electrical impedance tomography based on multilayer artificial neural network optimized by Hadamard product for human-chest models].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Electrical impedance tomography (EIT) is a non-radiation, non-invasive visual diagnostic technique. In order to improve the imaging resolution and the removing artifacts capability of the reconstruction algorithms for electrical impedance imaging in ...

[A deep blur learning-based motion artifact reduction algorithm for dental cone-beam computed tomography images].

Nan fang yi ke da xue xue bao = Journal of Southern Medical University
OBJECTIVE: We propose a motion artifact correction algorithm (DMBL) for reducing motion artifacts in reconstructed dental cone-beam computed tomography (CBCT) images based on deep blur learning.

Quantification of follicles in human ovarian tissue using image processing software and trained artificial intelligence†.

Biology of reproduction
Cancer survival rates in prepubertal girls and young women have risen in recent decades due to increasingly efficient treatments. However, many such treatments are gonadotoxic, causing premature ovarian insufficiency, loss of fertility, and ovarian e...

[Development of a grading diagnostic model for schistosomiasis-induced liver fibrosis based on radiomics and clinical laboratory indicators].

Zhongguo xue xi chong bing fang zhi za zhi = Chinese journal of schistosomiasis control
OBJECTIVE: To investigate the feasibility of developing a grading diagnostic model for schistosomiasis-induced liver fibrosis based on B-mode ultrasonographic images and clinical laboratory indicators.

Enhancing Meibography Image Analysis Through Artificial Intelligence-Driven Quantification and Standardization for Dry Eye Research.

Translational vision science & technology
PURPOSE: This study enhances Meibomian gland (MG) infrared image analysis in dry eye (DE) research through artificial intelligence (AI). It is comprised of two main stages: automated eyelid detection and tarsal plate segmentation to standardize meibo...

Generative artificial intelligence to produce high-fidelity blastocyst-stage embryo images.

Human reproduction (Oxford, England)
STUDY QUESTION: Can generative artificial intelligence (AI) models produce high-fidelity images of human blastocysts?

Prostate Cancer Risk Stratification by Digital Histopathology and Deep Learning.

JCO clinical cancer informatics
PURPOSE: Prostate cancer (PCa) represents a highly heterogeneous disease that requires tools to assess oncologic risk and guide patient management and treatment planning. Current models are based on various clinical and pathologic parameters includin...

3D evaluation model of facial aesthetics based on multi-input 3D convolution neural networks for orthognathic surgery.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Quantitative evaluation of facial aesthetics is an important but also time-consuming procedure in orthognathic surgery, while existing 2D beauty-scoring models are mainly used for entertainment with less clinical impact.

Smart Multimodal In-Bed Pose Estimation Framework Incorporating Generative Adversarial Neural Network.

IEEE journal of biomedical and health informatics
Monitoring in-bed pose estimation based on the Internet of Medical Things (IoMT) and ambient technology has a significant impact on many applications such as sleep-related disorders including obstructive sleep apnea syndrome, assessment of sleep qual...