Protozoa Optimized Deep Perceptual Enhancement Network for Lung CT Imaging
PDFAbstract
The precise feature extraction of small details from images of the human body is considered a challenge since fine details like small nodules and delicate vasculature are hard to see while the computed tomography scan is being conducted due to low contrast. Although various contrast enhancement methods have been introduced for better visibility of the images, they generally introduce more noise and edge artifacts. In this paper, a self-supervised Deep Perceptual Enhancement Network with an Artificial Protozoa Optimizer named APO-DPENet is proposed for optimizing the parameters of the image effectively. The results comparing the proposed method with other methods show a PSNR of 25.75308 dB, an SSIM of 0.95894, a CEI of 0.91385, and an EPI of 0.98960 units. The results indicate better contrast retention and edge preservation of the proposed method, along with improved noise removal capabilities. This suggests that the proposed method is robust enough for analysis.
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Erukala, Mahender, and Suresh Kumar Sanampudi. "Protozoa Optimized Deep Perceptual Enhancement Network for Lung CT Imaging." Journal of Innovative Image Processing 8, no. 1 (2026): 18-33. doi: 10.36548/jiip.2026.1.002
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Erukala, M., & Sanampudi, S. K. (2026). Protozoa Optimized Deep Perceptual Enhancement Network for Lung CT Imaging. Journal of Innovative Image Processing, 8(1), 18-33. https://doi.org/10.36548/jiip.2026.1.002
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Erukala, Mahender, et al. "Protozoa Optimized Deep Perceptual Enhancement Network for Lung CT Imaging." Journal of Innovative Image Processing, vol. 8, no. 1, 2026, pp. 18-33. DOI: 10.36548/jiip.2026.1.002.
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Erukala M, Sanampudi SK. Protozoa Optimized Deep Perceptual Enhancement Network for Lung CT Imaging. Journal of Innovative Image Processing. 2026;8(1):18-33. doi: 10.36548/jiip.2026.1.002
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M. Erukala, and S. K. Sanampudi, "Protozoa Optimized Deep Perceptual Enhancement Network for Lung CT Imaging," Journal of Innovative Image Processing, vol. 8, no. 1, pp. 18-33, Mar. 2026, doi: 10.36548/jiip.2026.1.002.
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Erukala, M. and Sanampudi, S.K. (2026) 'Protozoa Optimized Deep Perceptual Enhancement Network for Lung CT Imaging', Journal of Innovative Image Processing, vol. 8, no. 1, pp. 18-33. Available at: https://doi.org/10.36548/jiip.2026.1.002.
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@article{erukala2026,
author = {Mahender Erukala and Suresh Kumar Sanampudi},
title = {{Protozoa Optimized Deep Perceptual Enhancement Network for Lung CT Imaging}},
journal = {Journal of Innovative Image Processing},
volume = {8},
number = {1},
pages = {18-33},
year = {2026},
publisher = {Inventive Research Organization},
doi = {10.36548/jiip.2026.1.002},
url = {https://doi.org/10.36548/jiip.2026.1.002}
}
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Keywords
Lung CT Enhancement
DPE-Net
Artificial Protozoa Optimizer
Perceptual Quality
Residual Encoder Decoder
References
- Mohammed, Ibrahim Majid, and Nor Ashidi Mat Isa. "Contrast Limited Adaptive Local Histogram Equalization Method for Poor Contrast Image Enhancement." IEEE Access (2025).
- Kuran, Umut, and Emre Can Kuran. "Parameter Selection for CLAHE Using Multi-Objective Cuckoo Search Algorithm for Image Contrast Enhancement." Intelligent Systems with Applications 12 (2021): 200051.
- Panetta, Karen, Shreyas Kamath KM, Shishir Paramathma Rao, and Sos S. Agaian. "Deep Perceptual Image Enhancement Network for Exposure Restoration." IEEE Transactions on Cybernetics 53, no. 7 (2022): 4718-4731.
- Chen, Hu, Yi Zhang, Mannudeep K. Kalra, Feng Lin, Yang Chen, Peixi Liao, Jiliu Zhou, and Ge Wang. "Low-Dose CT with a Residual Encoder-Decoder Convolutional Neural Network." IEEE transactions on medical imaging 36, no. 12 (2017): 2524-2535.
- Guha, Ritam, Imran Alam, Suman Kumar Bera, Neeraj Kumar, and Ram Sarkar. "Enhancement of Image Contrast Using Selfish Herd Optimizer." multimedia tools and applications 81, no. 1 (2022): 637-657.
- Han, Dong, Liang Li, Xiaojie Guo, and Jiayi Ma. "Multi-Exposure Image Fusion Via Deep Perceptual Enhancement." Information Fusion 79 (2022): 248-262.
- Braik, Malik. "Hybrid Enhanced Whale Optimization Algorithm for Contrast and Detail Enhancement of Color Images." Cluster Computing 27, no. 1 (2024): 231-267.
- Zhou, Yuanping, Changqin Shi, Bingyan Lai, and Giorgos Jimenez. "Contrast Enhancement of Medical Images Using a New Version of the World Cup Optimization Algorithm." Quantitative imaging in medicine and surgery 9, no. 9 (2019): 1528.
- Wang, Xiaopeng, Václav Snášel, Seyedali Mirjalili, Jeng-Shyang Pan, Lingping Kong, and Hisham A. Shehadeh. "Artificial Protozoa Optimizer (APO): A Novel Bio-Inspired Metaheuristic Algorithm for Engineering Optimization." Knowledge-based systems 295 (2024): 111737.
- Erukala, Mahender, and Suresh Kumar Sanampudi. "Lumbar Spine MRI Images Quality Enhancement through Contrast Limited Adaptive Histogram Equalization." In 2024 5th International Conference on Communication, Computing & Industry 6.0 (C2I6), IEEE, 2024, 1-6.
- Wang, Hongfei, Ping Yang, Chuan Xu, Lei Min, Shuai Wang, and Bing Xu. "Lung CT Image Enhancement Based on Total Variational Frame and Wavelet Transform." International Journal of Imaging Systems and Technology 32, no. 5 (2022): 1604-1614.
- Zhang, Xiaowen, Yongfeng Ren, Guoyong Zhen, Yanhu Shan, and Chengqun Chu. "A Color Image Contrast Enhancement Method Based on Improved PSO." Plos one 18, no. 2 (2023): e0274054.
- Sharif, S. M. A., Rizwan Ali Naqvi, Mithun Biswas, and Woong-Kee Loh. "Deep Perceptual Enhancement for Medical Image Analysis." IEEE Journal of Biomedical and Health Informatics 26, no. 10 (2022): 4826-4836.
- Chen, Jia, Weiyu Yu, Jing Tian, Li Chen, and Zhili Zhou. "Image Contrast Enhancement Using an Artificial Bee Colony Algorithm." Swarm and Evolutionary Computation 38 (2018): 287-294.
- Abdulkadhim, Ahmed Abd Ali, and Amir Lakizadeh. "Hybrid Parallelism Image Encryption Algorithm Based on a Modified Blowfish Algorithm." International Journal of Intelligent Engineering & Systems 17, no. 6 (2024).
- Armato III, Samuel G., Geoffrey McLennan, Luc Bidaut, Michael F. McNitt‐Gray, Charles R. Meyer, Anthony P. Reeves, Binsheng Zhao et al. "The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): A Completed Reference Database of Lung Nodules on CT Scans." Medical physics 38, no. 2 (2011): 915-931.
