Biomedical image restoration using machine learning GPU acceleration approach for precision improvement

Bramah Hazela; Aarti; Arika Khandelwal; S. Soundararajan; Ruchi Vyas; A. Balaji

doi:10.53730/ijhs.v6nS3.5892

Authors

Bramah Hazela Assistant Professor, Department of Computer Science and Engineering, Amity School of Engineering and Technology, Amity University, Lucknow Campus, Lucknow – 22601
Aarti Assistant Professor, Computer Science and Information Technology, Central University of Haryana, Jant-Pali, Mahendergarh, Haryana, India, 123031
Arika Khandelwal Associate Professor, Department of Computer Science and Engineering, G.H.Raisoni College of engineering, Nagpur, Maharashtra – 440016
Soundararajan S. Professor, Department of Computer Science and Engineering, Velammal Institute of Technology, Chennai – 601204
Ruchi Vyas Assistant Professor, Department of Computer Science and Engineering, Geetanjali Institute of Technical studies, Udaipur, Rajasthan, India
A. Balaji Associate Professor, Department of Computer Science and Engineering, Guntur engineering college, Yanamadala, Andhra Pradesh 522019

Keywords:

image rebuilt, location of the lump, pulmonary movement, gpu, pulmonary carcinoma, radiation therapy

Abstract

Focusing the image in a single x-ray projection, an algorithm proposed for actual time volumetric image rebuilt and 3-dimensional location of the lump. Using the Principal Component Analysis (PCA) initialize the parameterized Deformation Vector Fields (DVF) of pulmonary movement. By adjusting the PCA coefficients, applied the DVF applied to optimize the reference image so that, the simulated projection of the rebuilt image matches the observed projection. The digital phantom & patient information was used to evaluate the technique. The phantom has an average relative image rebuilt error of 7.5 percent and a 3-dimensional location of the lump inaccuracy of 0.9 mm, correspondingly. The patient's location of the lump inaccuracy is less than 2 mm. On a GPU NVIDIA C1060, recreating a single volumetric image from every projection takes about 0.2 & 0.3 secs for patient and phantom. From a single image, clinical relevance could lead to reliable 3-dimensional lump tracking.

Downloads

Download data is not yet available.

References

Giraud P, Antoine M, Larrouy A, Milleron B, Callard P, De Rycke Y, Carette MF, Rosenwald JC, Cosset JM, Housset M, Touboul E. Evaluation of microscopic tumor extension in non–small-cell lung cancer for three-dimensional conformal radiotherapy planning. International Journal of Radiation Oncology* Biology* Physics. 2000 Nov 1;48(4):1015-24.

Karnan, B., Kuppusamy, A., Latchoumi, T. P., Banerjee, A., Sinha, A., Biswas, A., & Subramanian, A. K. (2022). Multi-response Optimization of Turning Parameters for Cryogenically Treated and Tempered WC–Co Inserts. Journal of The Institution of Engineers (India): Series D, 1-12.

Aroulanandam, V. V., Latchoumi, T. P., Bhavya, B., & Sultana, S. S. (2019). Object detection in convolution neural networks using iterative refinements. architecture, 15, 17.

Latchoumi, T. P., Reddy, M. S., & Balamurugan, K. (2020). Applied Machine Learning Predictive Analytics to SQL Injection Attack Detection and Prevention. European Journal of Molecular & Clinical Medicine, 7(02), 2020.

Banu, J. F., Muneeshwari, P., Raja, K., Suresh, S., Latchoumi, T. P., & Deepan, S. (2022, January). Ontology Based Image Retrieval by Utilizing Model Annotations and Content. In 2022 12th International Conference on Cloud Computing, Data Science & Engineering (Confluence) (pp. 300-305). IEEE.

Karnan, B., Kuppusamy, A., Latchoumi, T. P., Banerjee, A., Sinha, A., Biswas, A., & Subramanian, A. K. (2022). Multi-response Optimization of Turning Parameters for Cryogenically Treated and Tempered WC–Co Inserts. Journal of The Institution of Engineers (India): Series D, 1-12.

Garikapati, P., Balamurugan, K., Latchoumi, T. P., &Malkapuram, R. (2021). A Cluster-Profile Comparative Study on Machining AlSi 7/63% of SiC Hybrid Composite Using Agglomerative Hierarchical Clustering and K-Means. Silicon, 13, 961-972.

Romaguera LV, Mezheritsky T, Mansour R, Tanguay W, Kadoury S. Predictive online 3D target tracking with population-based generative networks for image-guided radiotherapy. International Journal of Computer Assisted Radiology and Surgery. 2021 Jun 10:1-3.

Garikapati, P. R., Balamurugan, K., Latchoumi, T. P., & Shankar, G. (2022). A Quantitative Study of Small Dataset Machining by Agglomerative Hierarchical Cluster and K-Medoid. In Emergent Converging Technologies and Biomedical Systems (pp. 717-727). Springer, Singapore.

Dr.P.Sivakumar, “Design and analysis the performance of real time content delivery network using beam scanning” journal of critical reviews, ISSN- 2394-5125 VOL 7, ISSUE 04, 2020.

Ezhilarasi, T. P., Dilip, G., Latchoumi, T. P., & Balamurugan, K. (2020). UIP—A Smart Web Application to Manage Network Environments. In Proceedings of the Third International Conference on Computational Intelligence and Informatics (pp. 97-108). Springer, Singapore.

Xue P, Fu Y, Ji H, Cui W, Dong E. Lung Respiratory Motion Estimation Based on Fast Kalman Filtering and 4D CT Image Registration. IEEE Journal of Biomedical and Health Informatics. 2020 Oct 12.

Latchoumi, T. P., Balamurugan, K., Dinesh, K., &Ezhilarasi, T. P. (2019). Particle swarm optimization approach for waterjet cavitation peening. Measurement, 141, 184-189.

Krieger M, Giger A, Salomir R, Bieri O, Celicanin Z, Cattin PC, Lomax AJ, Weber DC, Zhang Y. Impact of internal target volume definition for pencil beam scanned proton treatment planning in the presence of respiratory motion variability for lung cancer: A proof of concept. Radiotherapy and oncology. 2020 Apr 1;145:154-61.

Ting LL, Chuang HC, Liao AH, Kuo CC, Yu HW, Tsai HC, Tien DC, Jeng SC, Chiou JF. Tumor motion tracking based on a four-dimensional computed tomography respiratory motion model driven by an ultrasound tracking technique. Quantitative imaging in medicine and surgery. 2020 Jan;10(1):26.

Iwasawa T. Principles and Clinical Applications of Respiratory Motion Assessment Using 4D Computed Tomography and Magnetic Resonance Imaging. In Pulmonary Functional Imaging 2021 (pp. 91-106). Springer, Cham.

Latchoumi, T. P., Kalusuraman, G., Banu, J. F., Yookesh, T. L., Ezhilarasi, T. P., & Balamurugan, K. (2021, November). Enhancement in manufacturing systems using Grey-Fuzzy and LK-SVM approach. In 2021 IEEE International Conference on Intelligent Systems, Smart and Green Technologies (ICISSGT) (pp. 72-78). IEEE.

Romaguera LV, Plantefève R, Romero FP, Hébert F, Carrier JF, Kadoury S. Prediction of in-plane organ deformation during free-breathing radiotherapy via discriminative spatial transformer networks. Medical image analysis. 2020 Aug 1;64:101754.

Xu F, Xu W, Jones M, Keszthelyi B, Sedat J, Agard D, Mueller K. On the efficiency of iterative ordered subset reconstruction algorithms for acceleration on GPUs. Computer methods and programs in biomedicine. 2010 Jun 1;98(3):261-70.

Gregor J, Benson T. Computational analysis and improvement of SIRT. IEEE transactions on medical imaging. 2008 Jun 24;27(7):918-24.

Mattern, Shannon. Code and clay, data and dirt: Five thousand years of urban media. U of Minnesota Press, 2017.

Acemoglu, Daron, et al. A multi-risk SIR model with optimally targeted lockdown. Vol. 2020. Cambridge, MA: National Bureau of Economic Research, 2020.

Ricke, Jens, et al. "Impact of combined selective internal radiation therapy and sorafenib on survival in advanced hepatocellular carcinoma." Journal of hepatology 71.6 (2019): 1164-1174.

Liu, Yang, Chuanjiang He, and Yongfei Wu. "Variational model with kernel metric-based data term for noisy image segmentation." Digital Signal Processing 78 (2018): 42-55.

Liang, Jiuzhen, Min Li, and Cuicui Liao. "Efficient numerical schemes for Chan-Vese active contour models in image segmentation." Multimedia Tools and Applications 77.13 (2018): 16661-16684.

Dellmann MF, Jerg KI, Stratemeier J, Heiman R, Hesser JW, Aschenbrenner KP, Blessing M. Noise-robust breathing-phase estimation on marker-free, ultra low dose X-ray projections for real-time tumor localization via surrogate structures. Zeitschrift für Medizinische Physik. 2021 Jun 2.

Alina G, Krieger M, Jud C, Duetschler A, Salomir R, Bieri O, Bauman G, Nguyen D, Weber DC, Lomax AJ, Zhang Y. Liver-ultrasound based motion modelling to estimate 4D dose distributions for lung tumours in scanned proton therapy. Physics in Medicine & Biology. 2020 Dec 21;65(23):235050.

Sakly H, Mourad SA, Radhouane S, Tagina M. Medical decision making for 5D cardiac model: template matching technique and simulation of the fifth dimension. Computer methods and programs in biomedicine. 2020 Jul 1;191:105382.

Willett FR, Deo DR, Avansino DT, Rezaii P, Hochberg LR, Henderson JM, Shenoy KV. Hand knob area of premotor cortex represents the whole body in a compositional way. Cell. 2020 Apr 16;181(2):396-409.

Cai J, Wang Y, Liu A, McKeown MJ, Wang ZJ. Novel regional activity representation with constrained canonical correlation analysis for brain connectivity network estimation. IEEE transactions on medical imaging. 2020 Jan 30;39(7):2363-73.

Chang Y, Jiang Z, Segars WP, Zhang Z, Lafata K, Cai J, Yin FF, Ren L. A generative adversarial network (GAN)-based technique for synthesizing realistic respiratory motion in the extended cardiac-torso (XCAT) phantoms. Physics in Medicine & Biology. 2021 May 31;66(11):115018.