scholarly journals Coronary Arteries Segmentation Based on the 3D Discrete Wavelet Transform and 3D Neutrosophic Transform

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Shuo-Tsung Chen ◽  
Tzung-Dau Wang ◽  
Wen-Jeng Lee ◽  
Tsai-Wei Huang ◽  
Pei-Kai Hung ◽  
...  
Keyword(s):  
Coronary Arteries ◽  
Medical Image ◽  
Region Growing ◽  
Ground Truth ◽  
Discrete Wavelet ◽  
Segmentation Method ◽  
3D Dwt ◽  
Initial Segmentation ◽  
3D Discrete Wavelet Transform ◽  
3D Region Growing

Purpose. Most applications in the field of medical image processing require precise estimation. To improve the accuracy of segmentation, this study aimed to propose a novel segmentation method for coronary arteries to allow for the automatic and accurate detection of coronary pathologies.Methods. The proposed segmentation method included 2 parts. First, 3D region growing was applied to give the initial segmentation of coronary arteries. Next, the location of vessel information, HHH subband coefficients of the 3D DWT, was detected by the proposed vessel-texture discrimination algorithm. Based on the initial segmentation, 3D DWT integrated with the 3D neutrosophic transformation could accurately detect the coronary arteries.Results. Each subbranch of the segmented coronary arteries was segmented correctly by the proposed method. The obtained results are compared with those ground truth values obtained from the commercial software from GE Healthcare and the level-set method proposed by Yang et al., 2007. Results indicate that the proposed method is better in terms of efficiency analyzed.Conclusion. Based on the initial segmentation of coronary arteries obtained from 3D region growing, one-level 3D DWT and 3D neutrosophic transformation can be applied to detect coronary pathologies accurately.

scholarly journals An Efficient Lossless ROI Image Compression Using Wavelet-Based Modified Region Growing Algorithm

2018 ◽  
Vol 29 (1) ◽  
pp. 1063-1078
Author(s):  
P. Sreenivasulu ◽  
S. Varadarajan
Keyword(s):  
Wavelet Transform ◽  
Image Compression ◽  
Medical Image ◽  
Medical Images ◽  
Region Of Interest ◽  
Region Growing ◽  
Set Partitioning ◽  
Discrete Wavelet ◽  
Huffman Encoding ◽  
Encoding Method

Abstract Nowadays, medical imaging and telemedicine are increasingly being utilized on a huge scale. The expanding interest in storing and sending medical images brings a lack of adequate memory spaces and transmission bandwidth. To resolve these issues, compression was introduced. The main aim of lossless image compression is to improve accuracy, reduce the bit rate, and improve the compression efficiency for the storage and transmission of medical images while maintaining an acceptable image quality for diagnosis purposes. In this paper, we propose lossless medical image compression using wavelet transform and encoding method. Basically, the proposed image compression system comprises three modules: (i) segmentation, (ii) image compression, and (iii) image decompression. First, the input medical image is segmented into region of interest (ROI) and non-ROI using a modified region growing algorithm. Subsequently, the ROI is compressed by discrete cosine transform and set partitioning in hierarchical tree encoding method, and the non-ROI is compressed by discrete wavelet transform and merging-based Huffman encoding method. Finally, the compressed image combination of the compressed ROI and non-ROI is obtained. Then, in the decompression stage, the original medical image is extracted using the reverse procedure. The experimentation was carried out using different medical images, and the proposed method obtained better results compared to different other methods.

Three-Dimensional Segmentation Research of CT Abdominal Artery Image Sequence

2013 ◽  
Vol 791-793 ◽  
pp. 2048-2052
Author(s):  
Xiao Long Song ◽  
Qiao Wang ◽  
Zhen Gang Jiang
Keyword(s):  
Medical Image ◽  
Three Dimensional ◽  
Region Growing ◽  
Image Sequence ◽  
Segmentation Method ◽  
Clinical Diagnoses ◽  
Artery Disease ◽  
Segmentation Task ◽  
Three Dimensional Segmentation

As the role of medical imaging in clinical diagnoses and treatment has been more and more important, CT scan has been applied more widely. How to extract abdominal artery from CT image automatically and accurately has a significant value for abdominal artery disease. Because the medical image is of complexity and diversity, traditional segmentation method cannot complete the segmentation task very well. Therefore, this paper presents a method for extracting abdominal artery from CT images using three-dimensional region growing algorithm combined with image morphology. The experimental results show that the proposed method is an effective way for improving the accuracy of abdominal artery segmentation.

scholarly journals Medical Image Compression by Optimal Filter Coefficients Aided Transforms using Modified Rider Optimization Algorithm

2019 ◽  
Vol 9 (2) ◽  
pp. 5383-5393
Keyword(s):  
Image Compression ◽  
Optimization Algorithm ◽  
Medical Image ◽  
Region Of Interest ◽  
Region Growing ◽  
Superior Performance ◽  
Discrete Wavelet ◽  
Compression Process ◽  
Medical Image Compression ◽  
Segmentation Image

Owing to a large amount of images, image compression is requisite for minimizing the redundancies in image, and it offers efficient transmission and archiving of images. This paper presents a novel medical image compression model using intelligent techniques. The adopted medical image compression comprises of three major steps such as, Segmentation, Image compression, and Image decompression. Initially, the Region of Interest (ROI) and Non-ROI regions of the image are split by means of a Segmentation procedure using Modified Region Growing (MRG) algorithm. Moreover, the image compression process begins which is varied for both ROI and Non-ROI regions. On considering the ROI regions, the compression is carried out by Discrete Cosine Transform (DCT) model and SPIHT encoding method, whereas the compression of Non-ROI region is carried out by Discrete Wavelet Transform (DWT) and Merge-based Huffman encoding (MHE) methods. As a main contribution, this paper intends to deploy the optimized filter coefficients in both DCT and DWT techniques. Here, the optimization of both filter coefficients is performed using Modified Rider Optimization Algorithm (ROA) called Improvised Steering angle and Gear-based ROA (ISG-ROA). In the final step, decompression is done by implementing the reverse concept of compression process with similar optimized coefficients. The filter coefficients are tuned in such a way that the Compression Ratio (CR) should be minimum. In addition, the comparative analysis over the state-of-the-art models proves the superior performance of the proposed model.

Novel DWT/IDWT Architecture for 3D with Nine Stage 2D Parallel Processing using Split Distributed Arithmetic

2020 ◽  
Vol 20 (03) ◽  
pp. 2050017 ◽  
Author(s):  
S. S. Divakara ◽  
Sudarshan Patilkulkarni ◽  
Cyril Prasanna Raj
Keyword(s):  
Power Efficiency ◽  
High Speed ◽  
Discrete Wavelet ◽  
Distributed Arithmetic ◽  
Memory Space ◽  
Dynamic Memory ◽  
Wavelet Filters ◽  
Maximum Delay ◽  
3D Dwt ◽  
3D Discrete Wavelet Transform

Novel high-speed memory optimized distributed arithmetic (DA)-based architecture is developed and modeled for 3D discrete wavelet transform (DWT). The memory requirement for the proposed architecture is designed to [Formula: see text] pixel dynamic memory space and [Formula: see text] ROM. The proposed 3D-DWT architecture implements 9/7 Daubechies wavelet filters, synthesizes 7127 bytes of memory for temporary storage and uses 758 adders, 36 multiplexers of 16:1 and 36 up counter to realize the 3D-DWT hardware. The 3D-DWT engine is implemented and tested in a Xilinx FPGA Vertex5 XC5VLX155T with high area and power efficiency. The maximum delay in the timing path is 2.676[Formula: see text]ns and the 3D-DWT works at maximum frequency of 381[Formula: see text]MHz clock.

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