The Verdan classification of the finger extensor tendons. The anatomical distribution of extensor tendon regions: extrinsic extensors (regions VIII-X), wrist extensor region (region VII), dorsal hand (region VI), metacarpophalangeal (MCP) region (region V), proximal phalanx (region IV), proximal interphalangeal region (region III), middle phalanx (region II), and distal interphalangeal region (region I). The topography classification … Read more
※※Building a Medical Imaging Platform for Imaging Professionals※※ ◎Make Learning a Habit◎Make Knowledge an Essence ◎Make Expertise a Communication◎Let Us Become Lifelong Friends ※※※※※※※※※※※※※※※※※※※※※ A few days ago, I stumbled upon a piece of literature that piqued my interest while searching through references, so I decided to read it. Why was I interested? Initially, I … Read more
1. Tool Introduction 1.1 Main Features ACT（Atman Cloud Translation, Atman Cloud Translation）is an online translation tool focused on the medical field, helping professionals in the pharmaceutical industry and professional translators to break free from cumbersome CAT tools, quickly improving translation speed and accuracy. The self-developed medical machine translation engine by Atman is trained on hundreds … Read more
Today, I will share the improved model GER-UNet, which is based on the 2020 paper “Beyond CNNs: Exploiting Further Inherent Symmetries in Medical Images for Segmentation.” By understanding the ideas behind this model, similar improvements can be made based on VNet. 1. Limitations of Conventional Convolutional Networks 1. Conventional convolutional neural networks can only utilize … Read more
Today, I will share the improved model DC-UNet, which is based on the U-Net architecture. The improvement comes from the 2020 paper titled “DC-UNet: Rethinking the U-Net Architecture with Dual Channel Efficient CNN for Medical Images Segmentation.” By understanding the concept of this model, similar improvements can be made based on VNet. 1. Original UNet … Read more
Most applications of artificial intelligence in medicine utilize a single data modality to address tasks within a narrow scope, such as computed tomography (CT) scans or retinal photographs. However, clinicians integrate multi-source, multimodal data for diagnosis, prognosis assessment, and treatment planning. In this review, the authors explore the applications of multimodal datasets in healthcare, the … Read more
“Complementarity” and “Integration” Multimodal imaging unveils the mysteries of life from all angles 1 Understanding Life: Multimodal Biomedical Imaging Technology In recent years, rapidly developing biomedical imaging technologies can depict the structure and function of living organisms at different scales, such as in vivo, tissue, and molecular levels. However, single-modal representation is easily affected by … Read more
Iodinated contrast agents are widely used in CT angiography (CTA) examinations and play an irreplaceable role in the imaging diagnosis of vascular diseases throughout the body. However, there are risks of adverse reactions to injected contrast agents, contraindications, and high costs. Recently, a new study conducted by the First Medical Center of the PLA General … Read more
According to statistics, cardiovascular diseases are a leading cause of death worldwide. Coronary computed tomography angiography (CCTA) can clearly display the coronary arteries, accurately detect coronary plaques, and properly assess coronary lesions. With a negative predictive value close to 99% for coronary artery disease, CCTA has become an indispensable diagnostic tool for patients with cardiac … Read more
Deep Reconstruction Professor Zhang Yi, a doctoral supervisor from Sichuan University, once introduced the basic principles and classic methods of CT reconstruction, as well as the principles and current status of CT reconstruction. In this issue, he will take us to learn about his latest IEEE TMI paper on CT reconstruction using deep learning, which … Read more