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

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

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.

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