Medical Imaging
The demand for artificial intelligence (AI) in healthcare is rapidly increasing. However, significant challenges arise from data scarcity and privacy concerns, particularly in medical imaging. While existing generative models have achieved success in image synthesis and image-to-image translation tasks, there remains a gap in the generation of 3D semantic medical images. To address this gap, we introduce Med-DDPM, a diffusion model specifically designed for semantic 3D medical image synthesis, effectively tackling data scarcity and privacy issues.
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1603 Views
The morphological characteristics of skeletal muscles, such as fascicle orientation, fascicle length, and muscle thickness, contain valuable mechanical information that aids in understanding muscle contractility and excitation due to commands from the central nervous system. Ultrasound (US) imaging, a non-invasive measurement technique, has been employed in clinical research to provide visualized images that capture morphological characteristics. However, accurately and efficiently detecting the fascicle in US images is challenging.
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140 Views
This simulation dataset contains five types of data: resolutions, vessels, vessel stenosis, tumors, and shape combinations. There are a total of 1000 original binary images. Besides, we set different gray values on images with multiple connected domains to simulate different concentration of magnetic nanoparticles. Next, the images are subjected to operations such as image inversion and image rotation. The final dataset contains 20,000 images. we applied the X-space method based on the X-space theory and we generated the simulated image of magnetic particle imaging.
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193 Views
This Dataset used a non-invasive blood group prediction approach using deep learning. Rapid and meticulous prediction of blood type is a major step during medical emergency before supervising the red blood cell, platelet, and plasma transfusion. Any small mistake during transfer of blood can cause death. In conventional pathological assessment, the blood test is conducted using automated blood analyser; however, it results into time taking process.
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1443 Views
Use of medical devices in the magnetic resonance environment is regulated by standards that include the ASTM-F2213 magnetically induced torque. This standard prescribes five tests. However, none can be directly applied to measure very low torques of slender lightweight devices such as needles. Methods: We present a variant of an ASTM torsional spring method that makes a “spring” of 2 strings that suspend the needle by its ends. The magnetically induced torque on the needle causes it to rotate. The strings tilt and lift the needle.
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170 Views
— Medical image segmentation is a crucial aspect of medical image processing, and has been widely used in the detection and clinical diagnosis for brain, lung, liver, heart and other diseases. In this paper, we propose a novel multimodal mutual attention network, called MMAUNet, for medical image segmentation. MMA-UNet is divided into two parts. The first part obtains more highdimensional features by skip connection and improved network structure.
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208 Views
This robust dataset is extracted from the International Skin Imaging Collaboration (ISIC). Similar datasets are used for the annual ISIC Challenge, presenting an opportunity for the computer science community to produce algorithms that can outperform professional dermatology. The submitted dataset contains approximately 1,000 images of malignant melanomas, as well as approximately 1,000 images of benign melanomas.
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1831 Views
The dataset contains ungated free-breathing cardiac MRI scans with different image resolutions and slice thicknesses. Specifically, two low-resolution scans (2.27mm x 2.26mm resolution at 264 x 186 acquisition matrix size) are available with 10mm slice thickness and isotropic slice thickness, respectively, and a high-resolution scan (1.25mm x 1.26mm resolution at 480 x 334 acquisition matrix size) with 5mm slice thickness.
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593 Views
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39 Views