45748674-0223-4caa-8067-3a295a647080 beie director@blueeyesintelligence.org 10.35940/ijitee.B1031.14020125 10.1109/4233.640656Bankman, I.; Nizialek, T.; Simon, I.; Gatewood, O.; Weinberg, I.; Brody, W. Segmentation Algorithms for Detecting Microcalcifications in Mammograms. IEEE Trans. Inform. Techn. Biomed. 1997, 1, 141-149, DOI: https://doi.org/10.1109/4233.64065610.1109/TMI.2016.2553401Litjens, M.; Kooi, T.; Bejnordi, B.E.; Setio, A.A.; Ciompi, F.; Ghafoorian, M.; van der Laak, J.A.W.M.; van Ginneken, B.; Sánchez, C.I. Deep Learning in Medical Image Segmentation: A Review. IEEE Trans. Med. Imaging 2017, 35, 1235-1246, DOI: https://doi.org/10.1109/TMI.2016.255340110.1109/TBME.2008.2005957Kurkure, U.; Pednekar, A.; Muthupillai, R.; Flamm, S.; Kakadiaris, I. Localization and Segmentation of Left Ventricle in Cardiac Cine-MR Images. IEEE Trans. Biomed. Eng. 2009, 56, 1360-1370, DOI: https://doi.org/10.1109/TBME.2008.200595710.1109/TPAMI.2016.2572683Long, J.; Shelhamer, E.; Darrell, T. Fully Convolutional Networks for Semantic Segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 2015, 39, 640-651, DOI: https://doi.org/10.1109/TPAMI.2016.257268310.31590/ejosat.1041197Öztürk, N.; Öztürk, S. Bölütleme Tabanlı Yeni Görüntü İyileştirme Yöntemi. Avr. Bilim ve Teknol. Derg. 2021, 32, 975-981, DOI: https://doi.org/10.31590/ejosat.104119710.1109/83.902291Chan, T.F.; Vese, L.A. Region-Based Image Segmentation Using the Variational Methods: A Review. IEEE Trans. Image Process. 2001, 10, 942-953, DOI: https://doi.org/10.1109/83.902291Zhang, C.C.; Fang, J.D. Edge Detection Based on Improved Sobel Operator. In Proceedings of the International Conference on Computer Engineering and Information Systems, Advances in Computer Science Research (ACSR); Atlantis Press: 2016; Volume 52, pp. 129-132, https://www.atlantis-press.com/proceedings/ceis-16/2586784310.14257/ijseia.2013.7.5.11Min, B.S.; Lim, D.K.; Kim, S.J.; Lee, J.H. A Novel Method of Determining Parameters of CLAHE Based on Image Entropy. Int. J. Softw. Eng. Its Appl. 2013, 7, 113-120, https://www.researchgate.net/publication/274182255_A_Novel_Method_of_Determining_Parameters_of_CLAHE_Based_on_Image_Entropy10.1007/s11042-018-5878-8Garg, D.; Garg, N.K.; Kumar, M. Underwater Image Enhancement Using Blending of CLAHE and Percentile Methodologies. Multimedia Tools Appl. 2018, 77, 26545-26561, DOI: https://doi.org/10.1007/s11042-018-5878-810.1016/B978-0-12-336156-1.50061-6Zuiderveld, K. Adaptive Histogram Equalization and Its Variations. In Graphics Gems IV; Academic Press: 1994; pp. 474-485, DOI: https://doi.org/10.1016/B978-0-12-336156-1.50061-610.1109/TIP.2006.888338Agaian, S.S.; Silver, B.; Panetta, K.A. Transform Coefficient Histogram-Based Image Enhancement Algorithms Using Contrast Entropy. IEEE Trans. Image Process. 2007, 16, 615-624, DOI: https://doi.org/10.1109/TIP.2006.88833810.1016/j.patcog.2006.12.006Dale-Jones, R.; Tjahjadi, T. A Study and Modification of the Local Histogram Equalization Algorithm. Pattern Recognit. 2007, 26, 1373-1381, DOI: https://doi.org/10.1016/j.patcog.2006.12.00610.1109/ICIIP.2011.6108861Kaur, M.; Kaur, N.; Vig, J. Comparison of Adaptive Histogram Equalization and Contrast Limited Adaptive Histogram Equalization for Medical Image Enhancement. In Proceedings of the 2011 International Conference on Image Information Processing (ICIIP); IEEE: 2011; pp. 1-6, DOI: https://doi.org/10.1109/ICIIP.2011.610886110.1109/TBME.2008.919735Demirel, H.; Anbarjafari, G. Contrast Enhancement of Compressed and Decompressed Medical Images. IEEE Trans. Biomed. Eng. 2008, 55, 2163-2167, DOI: https://doi.org/10.1109/TBME.2008.91973510.1007/BF03168852Pisano, E.D.; Zong, L.; Johnston, R.E. Contrast Limited Adaptive Histogram Equalization Image Processing to Improve the Detection of Simulated Speculation in Dense Mammograms. J. Digit. Imaging 1998, 11, 193-200, DOI: https://doi.org/10.1007/BF0316885210.1088/0031-9155/58/13/R97Bauer, S.; Wiest, R.; Nolte, L.-P.; Reyes, M. A Survey of MRI-Based Medical Image Analysis for Brain Tumor Studies. Phys. Med. Biol. 2013, 58, R97-R129, DOI: https://doi.org/10.1088/0031-9155/58/13/R9710.1016/S1361-8415(01)80026-8Maintz, J.B.A.; Viergever, M.A. A Survey of Medical Image Registration. Med. Image Anal. 1998, 2, 1-36, DOI: https://doi.org/10.1016/S1361-8415(01)80026-810.35940/ijese.G9890.12040324Saha, T., & Vishal, Dr. K. (2024). A Study of Application of Digital Image Processing in Medical Field and Medical Image Segmentation by Edge Detection. In International Journal of Emerging Science and Engineering (Vol. 12, Issue 4, pp. 3-8). DOI: https://doi.org/10.35940/ijese.G9890.1204032410.1016/0031-3203(93)90135-JPal, N.R.; Pal, S.K. A Review of Image Segmentation Techniques. Pattern Recognit. 1993, 26, 1277-1294, DOI: https://doi.org/10.1016/0031-3203(93)90135-J10.35940/ijeat.E9309.069520Mirra, K. B., Pooja, P., Ranchani, S., & kumari, R. R. (2020). Fruit Quality Analysis using Image Processing. In International Journal of Engineering and Advanced Technology (Vol. 9, Issue 5, pp. 88-91). DOI: https://doi.org/10.35940/ijeat.E9309.06952010.1016/S0031-3203(01)00054-1Cheng, H.-D.; Jiang, X.H.; Sun, Y.; Wang, J. A Survey on Image Segmentation in Medical Imaging. J. Med. Syst. 2002, 26, 459-469, DOI: https://doi.org/10.1016/S0031-3203(01)00054-110.1080/08839514.2011.607009Rehman, A.; Saba, T. Document Skew Estimation and Correction: Analysis of Techniques, Common Problems and Possible Solutions. Appl. Artif. Intell. 2011, 25, 769-787, DOI: https://doi.org/10.1080/08839514.2011.60700910.1007/s10462-012-9319-1Rehman, A.; Saba, T. Features Extraction for Soccer Video Semantic Analysis: Current Achievements and Remaining Issues. Artif. Intell. Rev. 2012, 41, 451-461, DOI: https://doi.org/10.1007/s10462-012-9319-110.1016/j.compbiomed.2019.103385Bahrami, A.M.; Afifi, A.; Yazdani, E.; Mousavi, M.; Moradi, M.R. Automatic Segmentation of Arachnoid Cysts in Brain MRI Images Using Convolutional Neural Networks. Comput. Biol. Med. 2019, 113, 103385, DOI: https://doi.org/10.1016/j.compbiomed.2019.10338510.54105/ijipr.B1002.061221Sharma, Dr. K., & Garg, N. (2021). An Extensive Review on Image Segmentation Techniques. In Indian Journal of Image Processing and Recognition (Vol. 1, Issue 2, pp. 1-5). DOI: https://doi.org/10.54105/ijipr.B1002.06122110.35940/ijitee.B1051.1292S19Hema N, Laxmidevi Noolvi, M V Sudhamani, Liver and Tumor Segmentation Techniques for CT Abdominal Images. (2019). In International Journal of Innovative Technology and Exploring Engineering (Vol. 9, Issue 2S, pp. 555-560). DOI: https://doi.org/10.35940/ijitee.B1051.1292S1910.35940/ijrte.B1026.0982S1119A.A. Mariena, J.G.R. Sathiaseelan, Segmentation of Blood cell Images using Hybrid K-means with Cluster Center Estimation Technique. (2019). In International Journal of Recent Technology and Engineering (Vol. 8, Issue 2S11, pp. 160-163). DOI: https://doi.org/10.35940/ijrte.B1026.0982S1119