Auto-Segmentation of Neck Nodal Metastases Using Self-Distilled Masked Image Transformer on Longitudinal MR Images

Auto-Segmentation of Neck Nodal Metastases Using Self-Distilled Masked Image Transformer on Longitudinal MR Images

Potential of Self-Distilling Masked Image Transformer in Longitudinal MRI - Automatic Segmentation of Cervical Lymph Node Metastases Report Introduction In tumor radiotherapy, automatic segmentation technology promises to improve speed and reduce inter-reader variability caused by manual segmentation. In radiotherapy clinical practice, accurate and...

Efficient Deep Learning-Based Automated Diagnosis from Echocardiography with Contrastive Self-Supervised Learning

Breakthrough in Automated Echocardiogram Diagnosis via Deep Learning: A Comparative Study of Self-Supervised Learning Methods Research Background With the rapid development of artificial intelligence and machine learning technologies, their role in medical imaging diagnosis is becoming increasingly significant. In particular, Self-Supervised Learni...

Self-Supervised Learning of Accelerometer Data Provides New Insights for Sleep and Its Association with Mortality

Self-Supervised Learning of Accelerometer Data Provides New Insights for Sleep and Its Association with Mortality

Insights into the Association Between Sleep and Mortality Revealed by Self-supervised Learning of Wrist-worn Accelerometer Data In modern society, sleep is an essential basic activity for life, and its importance is self-evident. Accurately measuring and classifying sleep/wake states and different sleep stages is crucial for diagnosing sleep disord...

Diffusion Model Optimization with Deep Learning

Diffusion Model Optimization with Deep Learning

Dimond: A Study on Optimizing Diffusion Models through Deep Learning Academic Background In brain science and clinical applications, Diffusion Magnetic Resonance Imaging (dMRI) is an essential tool for non-invasively mapping the microstructure and neural connectivity of brain tissue. However, accurately estimating parameters of the diffusion signal...

Self-Supervised Deep Learning-Based Denoising for Diffusion Tensor MRI

Self-Supervised Deep Learning-Based Denoising for Diffusion Tensor MRI

Background Introduction Diffusion Tensor Magnetic Resonance Imaging (DTI) is a widely used neuroimaging technique for imaging the microstructure of brain tissues and white matter tracts. However, noise in Diffusion-Weighted Images (DWI) can reduce the accuracy of microstructural parameters derived from DTI data and also necessitate longer acquisiti...