Medical Imaging
该舌头图像数据集包含 300 张舌头图像。数据集中所有图像均由我们的图像采集设备采集,图像尺寸为576*768。手动分割被用作基本事实。
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The Lung Image Database Consortium image collection (LIDC-IDRI) consists of diagnostic and lung cancer screening thoracic computed tomography (CT) scans with marked-up annotated lesions. It is a web-accessible international resource for development, training, and evaluation of computer-assisted diagnostic (CAD) methods for lung cancer detection and diagnosis.
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MATLAB code for the proposed Single-shot Super-Resolution Phase Retrieval (SSR-PR) algorithm.
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Optical coherence tomography (OCT) is a powerful technology for monitoring and diagnosing eye diseases. However, speckle noise is not beneficialfor improving OCT image quality and further image analysis,such as segmentation of the retinal layer.Inspired by the rapid development of deep learning, several methods have been proposed for OCT denoising, and promising results have been obtained.
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This dataset includes two 3D models in .stl format:
- a reference frame (RF) for surgical navigation. It contains three branches for the attachment of spherical (passive) optical markers.
- a socket for the insertion of the RF. The socket model can be added to the design of a surgical guide.
These models were designed to be 3D printed with a Formlabs Form 2 3D printer in resin.
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The University of Turin (UniTO) released the open-access dataset Stoke collected for the homonymous Use Case 3 in the DeepHealth project (https://deephealth-project.eu/). UniToBrain is a dataset of Computed Tomography (CT) perfusion images (CTP).
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The region-based segmentation approach has been a major research area for many medical image applications. A vision guided autonomous system has used region-based segmentation information to operate heavy machinery and locomotive machines intended for computer vision applications. The dataset contains raw images in .png format fro brain tumor in various portions of brain.The dataset can be used fro training and testing. Images are calssified into three main regions as frontal lobe(level -1, level-2), optus-lobe(level-1), medula_lobe(level-1,level-2,level-3).
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The dataset contains 236 X-ray images, all of which include the top of the head to the middle of the thigh. The included patients are 18-80 years old, and treated to the department of orthopedics due to low back pain or spinal deformity. The original size of the X-ray images is around 3000×7000px.
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