Analyzing CT Scan Images towards the Early Detection of Lung Cancer using Medical Images based Edge Feature Preserving CT Scan Medical Image Coder (EZWT - EFPIC)


  • C. Thirumoorthi PSG College of Arts & Science
  • Manikandaprabhu P Sri Ramakrishna College of Arts & Science
  • P. V. Praveen Sundar Adhiparasakthi College of Arts and Science



CT lung cancer images, Cancer detection, Image Compression, Image processing, Medical image analysis


With the current improvements in virtual image processing techniques have received several benefits. Today, all of the scientific techniques produce virtual scientific pictures, through healthcare specialists analyze and diagnose the abnormality. The frequent view of scientific picture processing might also additionally appear simpler; however, it entails many challenges. As the scientific pics are interconnected with human lives, the laptop-aided scientific image processing structures have to be overcautious, if we want to eliminate inaccuracy rates. The utility of medical image processing techniques for the analysis of CT scan images similar to lung cancer cells has been gaining momentum in recent years. This paper discusses the use of a Transform Edge Feature preserving CT scan Medical Image Coder (EZWT - EFPIC) using Computed Tomography (CT) images to help in the early diagnosis of lung cancer. We discuss and explore the design and significance of an EZWT-EFPIC-CT image-processed model in cancer diagnosis.


Padmavati, S., and Vaibhav Meshram. "FPGA Implementation for Fractal Quadtree Image Compression." (2018).

Thirumoorthi, C., and Karthikeyan T. "Medical image compression technique with transform method for lung cancer CT scan image: A Review." International Journal of control Theory and Applications (IJCT), International science press, Serials publications 9, no. 26 (2016): 193-200.

Karthikeyan, T., and C. Thirumoorthi. "A Novel Approach on Discrete Cosion Transform Based Image Compression Technique for Lung Cancer." Biosciences Biotechnology Research Asia 13, no. 3 (2016): 1679-1688.

Karthikeyan, T., and C. Thirumoorthi. "A hybrid medical image compression technique for lung cancer." Indian Journal of Science and Technology 9, no. 39 (2016).

Karthikeyan, T., and C. Thirumoorthi. "A study on Discrete Wavelet Transform Compression Algorithm for Medical Iimages." Biomedical Research 28, no. 4 (2017): 1574-1580.

Karthikeyan, T., and C. Thirumoorthi. "Embedded Zero Tree Wavelet (EZW) algorithm based image transformation for easy optimization with HALIDE language." Int J Appl Eng Res 10 (2015): 1551-1554.

Thirumoorthi, C., and T. Karthikeyan. "Easy optimization of image transformation using sFFT algorithm with HALIDE language." In 2014 International Conference on Contemporary Computing and Informatics (IC3I), pp. 1188-1190. IEEE, 2014.

Karthikeyan, T., and C. Thirumoorthi. "A survey on embedded zero tree wavelet." International Journal of Computer Science (IJCS), ISSN (2014): 2348-6600.

Thirumoorthi. C., "Edge Based Compression Using Embedded Zero Wavelet Tree (EBC –EZWT) for Lung Cancer CT Scan Medical Image", International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 3, no.3, (2018): 653-659.

Stock, A. Michael, Gabriel Herl, Tomas Sauer, and Jochen Hiller. "Edge-preserving compression of CT scans using wavelets." Insight-Non-Destructive Testing and Condition Monitoring 62, no. 6 (2020): 345-351.

Pathak, Ketki C., Jignesh N. Sarvaiya, and Anand D. Darji. "Enhanced Hierarchical Prediction for Lossless Medical Image Compression in the Field of Telemedicine Application." In Biomedical Signal and Image Processing with Artificial Intelligence, pp. 207-229. Cham: Springer International Publishing, 2023.

Additional Files