scholarly journals Lost in Space: The Cost of Interruption During Search Through Volumetric Medical Images

2016 ◽  
Vol 16 (12) ◽  
pp. 1332
Author(s):  
Lauren Williams ◽  
Trafton Drew
Keyword(s):  
Medical Images ◽  
Volumetric Medical Images ◽  
The Cost

Statistical analysis of normal and abnormal dissymmetry in volumetric medical images

2000 ◽  
Vol 4 (2) ◽  
pp. 111-121 ◽  
Author(s):  
J.-P Thirion ◽  
S Prima ◽  
G Subsol ◽  
N Roberts
Keyword(s):  
Statistical Analysis ◽  
Medical Images ◽  
Volumetric Medical Images

scholarly journals Computational assessment of visual search strategies in volumetric medical images

2016 ◽  
Vol 3 (1) ◽  
pp. 015501 ◽  
Author(s):  
Gezheng Wen ◽  
Avigael Aizenman ◽  
Trafton Drew ◽  
Jeremy M. Wolfe ◽  
Tamara Miner Haygood ◽  
...  
Keyword(s):  
Visual Search ◽  
Medical Images ◽  
Search Strategies ◽  
Volumetric Medical Images

A Novel Blind Wavelet Base Watermarking of ECG Signals on Medical Images Using EZW Algorithm

2008 ◽  
pp. 1004-1015
Author(s):  
Mohammad Saleh Nambakhsh ◽  
M. Shiva
Keyword(s):  
Medical Images ◽  
Wavelet Coefficients ◽  
Ecg Signals ◽  
Multimedia Contents ◽  
Cost Of Health Care ◽  
Ezw Algorithm ◽  
Diagnostics System ◽  
The Cost ◽  
Efficient Memory ◽  
And Storage

Exchange of databases between hospitals needs efficient and reliable transmission and storage techniques to cut down the cost of health care. This exchange involves a large amount of vital patient information such as biosignals and medical images. Interleaving one form of data such as 1-D signal over digital images can combine the advantages of data security with efficient memory utilization (Norris, Englehart & Lovely, 2001), but nothing prevents the user from manipulating or copying the decrypted data for illegal uses. Embedding vital information of patients inside their scan images will help physicians make a better diagnosis of a disease. In order to solve these issues, watermark algorithms have been proposed as a way to complement the encryption processes and provide some tools to track the retransmission and manipulation of multimedia contents (Barni, Podilchuk, Bartolini & Delp, 2001; Vallabha, 2003). A watermarking system is based on an imperceptible insertion of a watermark (a signal) in an image. This technique is adapted here for interleaving graphical ECG signals within medical images to reduce storage and transmission overheads as well as helping for computer-aided diagnostics system. In this chapter, we present a new wavelet-based watermarking method combined with the EZW coder. The principle is to replace significant wavelet coefficients of ECG signals by the corresponding significant wavelet coefficients belonging to the host image, which is much bigger in size than the mark signal. This chapter presents a brief introduction to watermarking and the EZW coder that acts as a platform for our watermarking algorithm.

scholarly journals Lossless Compression of Medical Image Sequences Using a Resolution Independent Predictor and Block Adaptive Encoding

2019 ◽  
Vol 9 (2) ◽  
pp. 69-79 ◽  
Author(s):  
Urvashi Sharma ◽  
Meenakshi Sood ◽  
Emjee Puthooran
Keyword(s):  
Medical Images ◽  
Block Size ◽  
Lossless Compression ◽  
Experimental Tests ◽  
Threshold Value ◽  
Image Resolution ◽  
Coding Efficiency ◽  
Volumetric Medical Images ◽  
Adaptive Encoding ◽  
Block Based

The proposed block-based lossless coding technique presented in this paper targets at compression of volumetric medical images of 8-bit and 16-bit depth. The novelty of the proposed technique lies in its ability of threshold selection for prediction and optimal block size for encoding. A resolution independent gradient edge detector is used along with the block adaptive arithmetic encoding algorithm with extensive experimental tests to find a universal threshold value and optimal block size independent of image resolution and modality. Performance of the proposed technique is demonstrated and compared with benchmark lossless compression algorithms. BPP values obtained from the proposed algorithm show that it is capable of effective reduction of inter-pixel and coding redundancy. In terms of coding efficiency, the proposed technique for volumetric medical images outperforms CALIC and JPEG-LS by 0.70 % and 4.62 %, respectively.

scholarly journals Employing New Hybrid Adaptive Wavelet-Based Transform and Histogram Packing to Improve JP3D Compression of Volumetric Medical Images

Entropy ◽  
2020 ◽  
Vol 22 (12) ◽  
pp. 1385
Author(s):  
Roman Starosolski
Keyword(s):  
Compression Ratio ◽  
Medical Images ◽  
Three Dimensional ◽  
Discrete Wavelet ◽  
Adaptive Wavelet ◽  
Entropy Estimation ◽  
New Methods ◽  
Adaptive Parameter ◽  
3D Dwt ◽  
Volumetric Medical Images

The primary purpose of the reported research was to improve the discrete wavelet transform (DWT)-based JP3D compression of volumetric medical images by applying new methods that were only previously used in the compression of two-dimensional (2D) images. Namely, we applied reversible denoising and lifting steps with step skipping to three-dimensional (3D)-DWT and constructed a hybrid transform that combined 3D-DWT with prediction. We evaluated these methods using a test-set containing images of modalities: Computed Tomography (CT), Magnetic Resonance Imaging (MRI), and Ultrasound (US). They proved effective for 3D data resulting in over two times greater compression ratio improvements than competitive methods. While employing fast entropy estimation of JP3D compression ratio to reduce the cost of image-adaptive parameter selection for the new methods, we found that some MRI images had sparse histograms of intensity levels. We applied the classical histogram packing (HP) and found that, on average, it resulted in greater ratio improvements than the new sophisticated methods and that it could be combined with these new methods to further improve ratios. Finally, we proposed a few practical compression schemes that exploited HP, entropy estimation, and the new methods; on average, they improved the compression ratio by up to about 6.5% at an acceptable cost.

scholarly journals Segmentation of thin structures in volumetric medical images

2006 ◽  
Vol 15 (2) ◽  
pp. 354-363 ◽  
Author(s):  
M. Holtzman-Gazit ◽  
R. Kimmel ◽  
N. Peled ◽  
D. Goldsher
Keyword(s):  
Medical Images ◽  
Thin Structures ◽  
Volumetric Medical Images

scholarly journals OFCS: Optimized Framework of Compressive Sensing for Medical Images in Bottleneck Network Condition

2018 ◽  
Vol 8 (5) ◽  
pp. 2829
Author(s):  
Lakshminarayana M ◽  
Mrinal Sarvagya
Keyword(s):  
Compressive Sensing ◽  
Medical Image ◽  
Medical Images ◽  
Region Of Interest ◽  
Lossless Compression ◽  
Cost Effective ◽  
Signal Quality ◽  
Effective Solution ◽  
The Cost

Compressive sensing is one of teh cost effective solution towards performing compression of heavier form of signals. We reviewed the existing research contribution towards compressive sensing to find that existing system doesnt offer any form of optimization for which reason the signal are superiorly compressed but at the cost of enough resources. Therefore, we introduce a framework that optimizes the performance of the compressive sensing by introducing 4 sequential algorithms for performing Random Sampling, Lossless Compression for region-of-interest, Compressive Sensing using transform-based scheme, and optimization. The contribution of proposed paper is a good balance between computational efficiency and quality of reconstructed medical image when transmitted over network with low channel capacity. The study outcome shows that proposed system offers maximum signal quality and lower algorithm processing time in contrast to existing compression techniuqes on medical images.

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