Rapid Extraction and Compression of DICOM Data for Medical Image Geometric Modeling

2012 ◽  
Vol 433-440 ◽  
pp. 7511-7515
Author(s):  
Xue Mei Huang ◽  
Jin Chuan Wang
Keyword(s):  
Geometric Modeling ◽  
Medical Image ◽  
Transmission Efficiency ◽  
Memory Space ◽  
Block Coding ◽  
Rapid Extraction ◽  
Run Length Coding ◽  
And Storage ◽  
Compressed Data ◽  
Single Pixel

This paper presents a method of extracting and compressing required data from the DCM file for medical image geometric modeling. According to the characteristics of DICOM data, combining the idea of run-length coding with block coding, the rapid data compression and storage in RAM was realized finally. Compared with other coding methods, the encoding approach for DICOM data in this paper, not only saves the memory space and improves transmission efficiency, but also can read the required a single pixel, or part of pixel data from the compressed data conveniently.

scholarly journals Comparison Analysis with Huffman Algorithm and Goldbach Codes Algorithm in File Compression Text Using the Method Exponential Comparison

2020 ◽  
Vol 4 (1) ◽  
pp. 29
Author(s):  
Abu Sani Tanjung ◽  
Surya Darma Nasution
Keyword(s):  
Storage Process ◽  
Memory Space ◽  
Time Compression ◽  
Simple Compression ◽  
Huffman Algorithm ◽  
Original Size ◽  
Original File ◽  
Audio Video ◽  
And Storage ◽  
Compressed Data

With the development of technology at this time many people know about compression. In simple compression is a process to shrink the file from its original size. At this time compression applications that are often used are WinZip, WinRar, and 7-Zip, namely with the aim of compressing documents and saving space on memory or data transmission. Compressed data can be in the form of images, audio, video and text. The use of the Huffman algorithm and the Goldbach Codes algorithm in compressing text files is intended to provide enormous benefits in the sending and storage process and requires less memory space compared to uncompressed text. The algorithm starts by providing a string of inputs as input, how to produce an algorithm output in the form of a binary string or code that translates each input string, so that the string has a small number of bits compared to strings that are not compressed. Thus, the problem is how to obtain the code with sorted characters and frequency tables as input and shorter binary code as output. In applying the Huffman algorithm and the Goldbach Codes algorithm in compressing text files is very good, the results were not reduced from the original file or there was no reduction

scholarly journals Constant Transmission Efficiency Dimming Control Scheme for VLC Systems

Photonics ◽  
2020 ◽  
Vol 8 (1) ◽  
pp. 7
Author(s):  
Jia-Ning Guo ◽  
Jian Zhang ◽  
Gang Xin ◽  
Lin Li
Keyword(s):  
Visible Light Communication ◽  
Transmission Efficiency ◽  
Error Performance ◽  
Constant Weight ◽  
Block Coding ◽  
Control Scheme ◽  
Control Schemes ◽  
Indoor Wireless ◽  
Communication Function ◽  
Dimming Control

As a novel mode of indoor wireless communication, visible light communication (VLC) should consider the illumination functions besides the primary communication function. Dimming control is one of the most crucial illumination functions for VLC systems. However, the transmission efficiency of most proposed dimming control schemes changes as the dimming factor changes. A block coding-based dimming control scheme has been proposed for constant transmission efficiency VLC systems, but there is still room for improvement in dimming range and error performance. In this paper, we propose a dimming control scheme based on extensional constant weight codeword sets to achieve constant transmission efficiency. Meanwhile, we also provide a low implementation complexity decoding algorithm for the scheme. Finally, comparisons show that the proposed scheme can provide a wider dimming range and better error performance.

Application of Geometric Modeling in Visualizing the Medical Image Dataset

2020 ◽  
Vol 1 (5) ◽  
Author(s):  
Sinh Van Nguyen ◽  
Ha Manh Tran ◽  
Truong Son Le
Keyword(s):  
Geometric Modeling ◽  
Medical Image ◽  
Image Dataset

scholarly journals Anatomically Based Geometric Modelling Using Medical Image Data: Methods and Programs

2015 ◽  
Vol 9 (1) ◽  
pp. 126-131
Author(s):  
Monan Wang ◽  
Lei Sun ◽  
Yuming Liu
Keyword(s):  
Geometric Modeling ◽  
Medical Image ◽  
Structural Information ◽  
Geometric Model ◽  
Three Dimensional ◽  
Image Data ◽  
Region Growing ◽  
Reconstruction Algorithm ◽  
Medical Image Segmentation ◽  
Image Browsing

Geometric modeling software that can realize two-dimensional medical image browsing, preprocessing, and three-dimensional (3D) reconstruction is designed for modeling human organs. This software performs medical image segmentation using a method that combines the region growing and the interactive segmentation methods. The Marching Cubes surface reconstruction algorithm is used to obtain a 3D geometric model. The program is compiled using Visual Studio 2010. The software is employed to obtain the geometric model of the human femur, hipbone, and muscle. The geometric modeling results can accurately express the structural information of the skeleton and muscle.

scholarly journals Engineering Practical Lempel-Ziv Tries

2021 ◽  
Vol 26 (1) ◽  
pp. 1-47
Author(s):  
Diego Arroyuelo ◽  
Rodrigo Cánovas ◽  
Johannes Fischer ◽  
Dominik Köppl ◽  
Marvin Löbel ◽  
...  
Keyword(s):  
Factor Structure ◽  
Data Structures ◽  
Independent Interest ◽  
New Techniques ◽  
Memory Space ◽  
Compressed Data Structures ◽  
Regular Factor ◽  
Factorization Algorithms ◽  
Compressed Data

The Lempel-Ziv 78 ( LZ78 ) and Lempel-Ziv-Welch ( LZW ) text factorizations are popular, not only for bare compression but also for building compressed data structures on top of them. Their regular factor structure makes them computable within space bounded by the compressed output size. In this article, we carry out the first thorough study of low-memory LZ78 and LZW text factorization algorithms, introducing more efficient alternatives to the classical methods, as well as new techniques that can run within less memory space than the necessary to hold the compressed file. Our results build on hash-based representations of tries that may have independent interest.

scholarly journals A Novel Coding Based Dimming Scheme with Constant Transmission Efficiency in VLC Systems

2019 ◽  
Vol 9 (4) ◽  
pp. 803 ◽  
Author(s):  
Yu Zuo ◽  
Jian Zhang
Keyword(s):  
Visible Light ◽  
Data Transmission ◽  
Visible Light Communication ◽  
Transmission Efficiency ◽  
Reliable Data ◽  
Error Performance ◽  
Block Coding ◽  
Dimming Control ◽  
Transmitted Signal ◽  
Simulation Results

Visible light communication (VLC) has attracted tremendous attention due to two functions: communication and illumination. Both reliable data transmission and lighting quality need to be considered when the transmitted signal is designed. To achieve the desired levels of illumination, dimming control is an essential technology applied in VLC systems. In this paper, we propose a block coding-based dimming scheme to construct the codeword set, where dimming control can be achieved by changing the ratio of two levels (ON and OFF) based on on-off keying (OOK) modulation. Simulation results show that the proposed scheme can maintain good error performance with constant transmission efficiency under various dimming levels.

A Separate 3D Convolutional Neural Network Architecture for 3D Medical Image Semantic Segmentation

2019 ◽  
Vol 9 (8) ◽  
pp. 1705-1716
Author(s):  
Shidu Dong ◽  
Zhi Liu ◽  
Huaqiu Wang ◽  
Yihao Zhang ◽  
Shaoguo Cui
Keyword(s):  
Neural Network ◽  
Image Segmentation ◽  
Brain Tumor ◽  
Network Architecture ◽  
Medical Image ◽  
Negative Impact ◽  
Class Imbalance ◽  
Semantic Segmentation ◽  
Medical Image Segmentation ◽  
Memory Space

To exploit three-dimensional (3D) context information and improve 3D medical image semantic segmentation, we propose a separate 3D (S3D) convolution neural network (CNN) architecture. First, a two-dimensional (2D) CNN is used to extract the 2D features of each slice in the xy-plane of 3D medical images. Second, one-dimensional (1D) features reassembled from the 2D features in the z-axis are input into a 1D-CNN and are then classified feature-wise. Analysis shows that S3D-CNN has lower time complexity, fewer parameters and less memory space requirements than other 3D-CNNs with a similar structure. As an example, we extend the deep convolutional encoder–decoder architecture (SegNet) to S3D-SegNet for brain tumor image segmentation. We also propose a method based on priority queues and the dice loss function to address the class imbalance for medical image segmentation. The experimental results show the following: (1) S3D-SegNet extended from SegNet can improve brain tumor image segmentation. (2) The proposed imbalance accommodation method can increase the speed of training convergence and reduce the negative impact of the imbalance. (3) S3D-SegNet with the proposed imbalance accommodation method offers performance comparable to that of some state-of-the-art 3D-CNNs and experts in brain tumor image segmentation.

Enhancing the Security of Exchanging and Storing DICOM Medical Images on the Cloud

2018 ◽  
Vol 8 (1) ◽  
pp. 154-172 ◽  
Author(s):  
O. Dorgham ◽  
Banan Al-Rahamneh ◽  
Ammar Almomani ◽  
Moh'd Al-Hadidi ◽  
Khalaf F. Khatatneh
Keyword(s):  
Digital Signature ◽  
Medical Image ◽  
Medical Images ◽  
Software Implementation ◽  
Symmetric Encryption ◽  
Hybrid Encryption ◽  
Encryption Algorithms ◽  
Asymmetric Encryption ◽  
And Storage ◽  
Image Format

Medical image information can be exchanged remotely through cloud-based medical imaging services. Digital Imaging and Communication in Medicine (DICOM) is considered to be the most commonly used medical image format among hospitals. The objective of this article is to enhance the secure transfer and storage of medical images on the cloud by using hybrid encryption algorithms, which are a combination of symmetric encryption algorithms and asymmetric encryption algorithms that make the encryption process faster and more secure. To this end, three different algorithms are chosen to build the framework. These algorithms are simple and suitable for hardware or software implementation because they require low memory and low computational power yet provide high security. Also, security was increased by using a digital signature technique. The results of the analyses showed that for a DICOM file with size 12.5 Mb, 2.957 minutes was required to complete the process. This was totaled from the encryption process took 1.898 minutes, and the decryption process took 1.059 minutes.

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