Computer-Aided Diagnosis of Pathological Section for Eosinophilic Gastroenteritis

Zhenzhen Wan; Chunxue Li; Fang Liu; Shaoyong Zhang; Shuai Han

doi:10.3788/LOP57.201701

[1] Chen F. Research on the typing and parallelization of pathological tissue section images[D]. Guiyang: Guizhou University, 1-7(2019).

[2] Soille P J, Ansoult M M. Automated basin delineation from digital elevation models using mathematical morphology[J]. Signal Processing, 20, 171-182(1990). http://www.sciencedirect.com/science/article/pii/016516849090127K

[3] González-Betancourt A, Rodríguez-Ribalta P, Meneses-Marcel A et al. Automated marker identification using the Radon transform for watershed segmentation[J]. IET Image Processing, 11, 183-189(2017).

[4] Koyuncu C F, Akhan E, Ersahin T et al. Iterative h-minima-based marker-controlled watershed for cell nucleus segmentation[J]. Cytometry. Part A : the journal of the International Society for Analytical Cytology, 89, 338-349(2016).

[5] Guo J J, Xu M, Kong L A[J]. People counting algorithm based on improved HOG features Information Technology and Informatization, 2019, 81-84.

[6] Riggle K M, Wahbeh G, Williams E M et al. Perforated duodenal ulcer: an unusual manifestation of allergic eosinophilic gastroenteritis[J]. World Journal of Gastroenterology, 21, 12709(2015).

[7] Zhao Q H, Wang Y H, Gao X Y et al. Filtering evaluation method of phase images based on smooth spline fitting[J]. Acta Optica Sinica, 38, 0815020(2018).

[8] Zhang J G, Feng W Z, Hu C H et al. Image segmentation method for forestry unmanned aerial vehicle pest monitoring based on composite gradient watershed algorithm[J]. Transactions of the Chinese Society of Agricultural Engineering, 33, 93-99(2017).

[9] Gush T. Bukhari S B A, Haider R, et al. Fault detection and location in a microgrid using mathematical morphology and recursive least square methods[J]. International Journal of Electrical Power & Energy Systems, 102, 324-331(2018).

[10] Yu W H. A mathematical morphology based method for hierarchical clustering analysis of spatial points on street networks[J]. Applied Soft Computing, 85, 105785(2019).

[11] Stringhini R M, Welfer D, Dornellas M C et al. A mathematical morphology-based filter for noise reduction and detail preservation in low-dose dental CT images[J]. Studies in health technology and informatics, 264, 253-257(2019).

[12] Das J K, Choudhury P P, Chaturvedi N et al. Ranking and clustering of Drosophila olfactory receptors using mathematical morphology[J]. Genomics, 111, 549-559(2019).

[13] Shirazi S H, Umar A I, Naz S et al. Efficient leukocyte segmentation and recognition in peripheral blood image[J]. Technology and Health Care, 24, 335-347(2016).

[14] Anter A M, Hassenian A E. CT liver tumor segmentation hybrid approach using neutrosophic sets, fast fuzzy c-means and adaptive watershed algorithm[J]. Artificial Intelligence in Medicine, 97, 105-117(2019).

[15] Gamarra M, Zurek E, Escalante H J et al. Split and merge watershed: a two-step method for cell segmentation in fluorescence microscopy images[J]. Biomedical Signal Processing and Control, 53, 101575(2019).

[16] Pang C Y, Liu J K. Improved LFP algorithm on leukocyte image texture feature extraction and recognition[J]. Acta Photonica Sinica, 42, 1375-1380(2013).

[17] Hou H, Shi Y X. Application of the improved watershed algorithm based on distance transform in white blood cell segmentation[J]. Computing Technology and Automation, 35, 81-84(2016).