Aiding 3D Hyperthermia Planning by the Use of Combined Modelling and Visualization of Different Medical Image Data Sets

1993 ◽  
pp. 695-700
Author(s):  
Marcus Rudolph ◽  
Ulf Jackisch
Keyword(s):  
Medical Image ◽  
Image Data ◽  
Data Sets ◽  
Medical Image Data

scholarly journals Implementation and evaluation of segmentation algorithms according to multimodal imaging in personalized medicine

2017 ◽  
Vol 3 (2) ◽  
pp. 207-210
Author(s):  
Manuel Stich ◽  
Jeannine Vogt ◽  
Michaela Lindner ◽  
Ralf Ringler
Keyword(s):  
Personalized Medicine ◽  
Multimodal Imaging ◽  
Medical Image ◽  
Current Trend ◽  
Image Data ◽  
Surrounding Tissue ◽  
Artificial Noise ◽  
Data Sets ◽  
Segmentation Methods ◽  
Medical Image Data

AbstractMultimodal imaging is gaining in importance in the field of personalized medicine and can be described as a current trend in medical imaging diagnostics. The segmentation, classification and analysis of tissue structures is essential. The goal of this study is the evaluation of established segmentation methods on different medical image data sets acquired with different diagnostic procedures. Established segmentation methods were implemented using the latest state of the art and applied to medical image data sets. In order to benchmark the segmentation performance quantitatively, medical image data sets were superimposed with artificial Gaussian noise, and the mis-segmentation as a function of the image SNR or CNR was compared to a gold standard. The evaluation of the image segmentation showed that the best results of pixel-based segmentation (< 3%) can be achieved with methods of machine learning, multithreshold and advanced level-set method - even at high artificial noise (SNR< 18). Finally, the complexity of the object geometry and the contrast of the ROI to the surrounding tissue must also be considered to select the best segmentation algorithm.

scholarly journals Design and Implementation of Compressed Medical Data over an Authenticated Secured

2020 ◽  
Vol 9 (3) ◽  
pp. 1543-1548
Keyword(s):  
Medical Image ◽  
Research Work ◽  
Health Sector ◽  
Image Data ◽  
Medical Data ◽  
Information Network ◽  
Design And Implementation ◽  
Simulation Results ◽  
Medical Image Data ◽  
Secure Transmission

Ideally, secure transmission of medical image data is one of the major challenges in health sector. The National Health Information Network has to protect the data in confidential manner. Storage is also one of the basic concern along with secure transmission. In this paper we propose an algorithm that supports confidentiality, authentication and integrity implementation of the scrambled data before transmitting on the communication medium. Before communication the data is compressed while keeping data encrypted. The research work demonstrate with simulation results. The results shows that the proposed work effectively maintains confidentiality, authentication and integrity. The experimental results evaluated medical image quality like PSNR, MSE, SC, and NAEetc.

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