Closed-loop Optogenetic Neuromodulation Enables High-Fidelity Fatigue-Resistant Muscle Control

Closed-loop Optogenetic Neuromodulation Enables High-Fidelity Fatigue-Resistant Muscle Control

High-Fidelity Fatigue-Resistant Muscle Control Through Closed-Loop Optogenetic Neural Modulation Background Introduction Skeletal muscle is the biological actuator for almost all movements in animals and humans. However, under various neurological conditions, the communication pathways between the central nervous system and neuromuscular components...

Simultaneous, Cortex-Wide Dynamics of Up to 1 Million Neurons Reveal Unbounded Scaling of Dimensionality with Neuron Number

Simultaneously Recording Up to a Million Neurons’ Cortical Dynamics Reveals Unbounded Scaling of Neuronal Quantity and Dimensionality Summary This scientific report titled “Simultaneously Recording Up to a Million Neurons’ Cortical Dynamics Reveals Unbounded Scaling of Neuronal Quantity and Dimensionality,” published in the journal Neuron (Volume 1...

A Magnetic Particle Imaging Approach for Minimally Invasive Imaging and Sensing with Implantable Bioelectronic Circuits

Minimally Invasive Imaging and Sensing Methods Based on Magnetic Particle Imaging and the Application of Implanted Electronic Circuits Academic Background In modern medicine, minimally invasive and biocompatible implantable bioelectronics are widely used for long-term monitoring of physiological processes inside the body. However, methods for imagi...

Semi-Supervised Thyroid Nodule Detection in Ultrasound Videos

Semi-Supervised Thyroid Nodule Detection in Ultrasound Videos

Research Report on Semi-Supervised Detection of Thyroid Nodules in Ultrasound Videos Research Background Thyroid nodules are common thyroid diseases. Early screening and diagnosis of thyroid nodules typically rely on ultrasound examinations, a common non-invasive detection method used for detecting various diseases such as thyroid nodules, breast c...

Bilateral Supervision Network for Semi-Supervised Medical Image Segmentation

Bilateral Supervision Network for Semi-Supervised Medical Image Segmentation

Research Background and Motivation Medical image segmentation is of great significance in the image analysis of anatomical structures and lesion areas, as well as in clinical diagnosis. However, existing fully supervised learning methods rely on a large amount of annotated data, and obtaining pixel-level annotated data for medical images is costly ...

3D/2D Vessel Registration Based on Monte Carlo Tree Search and Manifold Regularization

3D/2D Vessel Registration Based on Monte Carlo Tree Search and Manifold Regularization

Research on 3D/2D Vascular Registration Based on Monte Carlo Tree Search and Manifold Regularization In interventional vascular surgery, enhanced intraoperative real-time imaging technology can compensate for the shortcomings of DSA navigation, such as the lack of depth information and excessive use of toxic contrast agents, by projecting preoperat...

Exploration of Coincidence Detection of Cascade Photons to Enhance Preclinical Multi-Radionuclide SPECT Imaging

Exploration of Coincidence Detection of Cascade Photons to Enhance Preclinical Multi-Radionuclide SPECT Imaging

Exploration of Coincidence Detection of Cascade Photons to Improve Multi-Nuclide SPECT Imaging Radiopharmaceutical Therapy (RPT) has garnered increasing interest in recent years, especially in SPECT imaging involving the simultaneous use of multiple tracers. Traditional imaging methods are prone to scattering and crosstalk from different energy γ-r...

Whole Reconstruction-Free System Design for Direct Positron Emission Imaging from Image Generation to Attenuation Correction

Whole Reconstruction-Free System Design for Direct Positron Emission Imaging from Image Generation to Attenuation Correction

Background Introduction A hundred years ago, Hevesy first proposed using radioactive tracers as biological markers in plants, later validated through experiments in rats. This discovery propelled the development of nuclear medicine and molecular imaging in the biomedical field, making it possible to quantitatively visualize biological processes at ...

AI-based Denoising of Head Impact Kinematics Measurements with Convolutional Neural Network for Traumatic Brain Injury Prediction

Research and Application of Denoising Head Impact Kinematics Measurement Based on Convolutional Neural Networks Research Background Mild Traumatic Brain Injury (MTBI) is a global health threat. Humans often face the risk of MTBI in situations such as falls, traffic accidents, and sports. According to statistics, there were over 27 million brain inj...

Study on the Safety and Efficacy of Algorithmically Controlled Electroporation for Treating Spontaneous Equine Melanoma

Study on the Safety and Efficacy of Algorithmically Controlled Electroporation for Treating Spontaneous Equine Melanomas In recent years, electroporation, specifically irreversible electroporation (IRE), has shown significant potential as a non-thermal ablation technique in tumor treatment. Compared to traditional thermal ablation methods, IRE can ...