TY - GEN
T1 - Assessment of Image Quality Metrics by Means of Various Preprocessing Filters for Lung CT Scan Images
AU - Saxena, Sugandha
AU - Prasad, S. N.
AU - Murthy, T. S.Deepthi
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
PY - 2022
Y1 - 2022
N2 - Lung cancer is the most predominant and lethal growth around the world. Lung Computerized Tomography (CT) scan images have been contributing enormously to clinical research and diagnosis. Although due to the presence of artifacts, noise and blurring effects, the CT images produce a degraded output of the actual part under diagnosis. Hence, application of preprocessing filters on CT images proves crucial to reduce the noise and improve the quality of image. In this paper, we evaluate the image quality by exploring various parameters such as Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), Speckle reduction and Mean Preservation Index (SMPI) and Speckle Suppression Index (SSI), thereby measuring the performance of different filters.
AB - Lung cancer is the most predominant and lethal growth around the world. Lung Computerized Tomography (CT) scan images have been contributing enormously to clinical research and diagnosis. Although due to the presence of artifacts, noise and blurring effects, the CT images produce a degraded output of the actual part under diagnosis. Hence, application of preprocessing filters on CT images proves crucial to reduce the noise and improve the quality of image. In this paper, we evaluate the image quality by exploring various parameters such as Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), Speckle reduction and Mean Preservation Index (SMPI) and Speckle Suppression Index (SSI), thereby measuring the performance of different filters.
UR - https://www.scopus.com/pages/publications/85130285647
UR - https://www.scopus.com/inward/citedby.url?scp=85130285647&partnerID=8YFLogxK
U2 - 10.1007/978-981-16-8542-2_5
DO - 10.1007/978-981-16-8542-2_5
M3 - Conference contribution
AN - SCOPUS:85130285647
SN - 9789811685415
T3 - Lecture Notes in Electrical Engineering
SP - 59
EP - 70
BT - International Conference on Artificial Intelligence and Sustainable Engineering - Select Proceedings of AISE 2020
A2 - Sanyal, Goutam
A2 - Travieso-González, Carlos M.
A2 - Awasthi, Shashank
A2 - Pinto, Carla M.
A2 - Purushothama, B. R.
PB - Springer Science and Business Media Deutschland GmbH
T2 - International Conference on Artificial Intelligence and Sustainable Engineering, AISE 2020
Y2 - 27 November 2020 through 29 November 2020
ER -
