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Cervical Cell Classification Based Exclusively on Nucleus Features.

, and . ICIAR (2), volume 7325 of Lecture Notes in Computer Science, page 483-490. Springer, (2012)

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Accurate Localization of Cell Nuclei in PAP Smear Images using Gradient Vector Flow Deformable Models., , and . BIOSIGNALS, page 284-289. INSTICC Press, (2010)Combining shape, texture and intensity features for cell nuclei extraction in Pap smear images., , and . Pattern Recognit. Lett., 32 (6): 838-853 (2011)Cervical Cell Classification Based Exclusively on Nucleus Features., and . ICIAR (2), volume 7325 of Lecture Notes in Computer Science, page 483-490. Springer, (2012)Inflammatory Cell Extraction and Nuclei Detection in Pap Smear Images., , , , , and . IJEHMC, 6 (2): 27-43 (2015)An efficient adaptive thresholding scheme for signal decoding in NLOS VLC systems., , , , , , and . MeditCom, page 378-382. IEEE, (2021)Sipakmed: A New Dataset for Feature and Image Based Classification of Normal and Pathological Cervical Cells in Pap Smear Images., , , , , and . ICIP, page 3144-3148. IEEE, (2018)Spatial Transformer Generative Adversarial Network for Image Super-Resolution., , , and . ICIAP (1), volume 14233 of Lecture Notes in Computer Science, page 399-411. Springer, (2023)Splitting of overlapping nuclei guided by robust combinations of concavity points., , and . Medical Imaging: Image Processing, volume 9034 of SPIE Proceedings, page 903431. SPIE, (2014)An Automated Method for Lumen and Media-Adventitia Border Detection in a Sequence of IVUS Frames., , , and . IEEE Trans. Inf. Technol. Biomed., 8 (2): 131-141 (2004)Segmentation of cell clusters in Pap smear images using intensity variation between superpixels., , and . IWSSIP, page 184-187. IEEE, (2015)