'Medical image' presentation slideshows

The introduction of sectional anatomy

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833 views • 54 slides

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A Large Scale Medical Volume Rendering on Clustering System

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Medical Image Segmentation & Computer-Aided Diagnosis

Medical Image Segmentation & Computer-Aided Diagnosis. Wee-Kheng Leow Dept. of Computer Science National University of Singapore. Introduction. Main medical imaging topics: Segmentation Classification Quantification Visualization Main applications: Computer-aided diagnosis

666 views • 30 slides

Natinai Jinsakul 1,2 ; Cheng- Fa Tsai 2

2019 2nd Asia Pacific Conference on Medical and Health Science (APCMHS 2019), June 1-3, 2019 Seoul, South Korea. Medical Image Preprocessing and Convolutional Neural Network for Colorectal Cancer Image Classification. Natinai Jinsakul 1,2 ; Cheng- Fa Tsai 2

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398 views • 26 slides

Protecting the Exchange of Medical Images in Healthcare Process Integration with Web Services

Protecting the Exchange of Medical Images in Healthcare Process Integration with Web Services. Introduction. Medical images exist in electronic format for easy storage and maintenance promote high quality healthcare services for patients a picture is worth a thousand words

360 views • 22 slides

Silver Age Guaranteed Notes The future of Seniors

303 views • 19 slides

NA-MIC Community

241 views • 17 slides

Computer Science @CSI

348 views • 16 slides

GVF Snake and Active Shape Model

GVF Snake and Active Shape Model. Chunlei Han Turku PET Centre Sep 14, 2005, Turku, Finland. Content. Summary of GVF snake Feature of medical image Active shape model (ASM) PET heart search algorithm. Summary of GVF snake 1. Tranditional force field. GVF force field.

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Image Annotation using XML and MPEG-7

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Predicting The Future

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allied_medical_imaging_software

Medical diagnostics have advanced enormously, and things are a lot easier for doctors because the techniques used in the diagnosis is highly advanced. New technical advances in medical diagnostics, especially in the field of medical imaging techniques have entirely changed the way the disease is being treated now. One of the most promising advancements in the treatment of cancer is through new and relatively well know methods of diagnosis, namely the "Positron Emission Tomography" or the PET CT scan as it is generally known. The PET CT scan is one way to identify cancer, or lymphoma as it is better known. Visit https://www.alliedbusiness.co.in/ for more details.

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ROI Determination and Compression in MRI Using Gradient Method with CUDA

Due to the large use of MRI in hospitals, large storage areas are needed to store these images. Also, if you want to access these images over the system repeatedly, a large bandwidth is required. To solve this problem, it will be necessary to compress and store the medical imaging system quickly and without disruption. It has been seen that in the studies made on MRIs, the non used regions NON ROI occupy a large space and the image size can be reduced significantly when the unnecessary area in the image is cleaned. In this method developed with CUDA, the region of interest ROI in the MRI is detected by sending a 3x3 Kirsch filter matrix to the CUDA cores and the NON ROI region is extracted from the image with CUDA. These operations are first executed by the serial application on CPU, then by a parallel application on GPU. As a result, the application running on the GPU produced 34 times faster results than the application on the CPU. When images are compressed with this new improved method, it takes up 89 less than the original image size and 15 less than the original compressed image. Mahmut u00c3nver "ROI Determination and Compression in MRI Using Gradient Method with CUDA" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-1 , December 2018, URL: https://www.ijtsrd.com/papers/ijtsrd20263.pdf Paper URL: https://www.ijtsrd.com/computer-science/parallel-computing/20263/roi-determination-and-compression-in-mri-using-gradient-method-with-cuda/mahmut-u00fcnver

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Imaging Basics

Imaging Basics. A medical image is a 2D or 3D distribution of signals which represent properties of an object. The purpose of medical images include: Structure e.g. chest X-ray Organ function e.g. renal scan A combination of the above e.g. functional MR

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Medical Image Analysis Integrated & Standalone Market to Exceed US$ 3.6 Billion By 2022

The Global Medical Image Analysis Integrated & Standalone Market is expected to exceed more than US$ 3.6 billion by 2022 and will grow at a CAGR of more than 7.5% in the given forecast period.

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IJETR

ER Publication, IJETR, IJMCTR, Journals, International Journals, High Impact Journals, Monthly Journal, Good quality Journals, Research, Research Papers, Research Article, Free Journals, Open access Journals, erpublication.org, Engineering Journal, Science Journals,

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DICOM image viewer

Thus, there are much more things that will entice you to go with a hybrid solution for your medical imaging. Also, itu2019s good for DICOM image viewer when you use a hybrid solution.

46 views • 3 slides