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  • br We believe that the obtained results

    2022-04-28


    We believe that the obtained results are important for special-ists interested in the study of colorectal cancer, in that they al-low for detailed analyses involving different types of features and classifiers. The indications of the best associations with histolog-ical properties are also relevant contributions. In future work, it Thapsigargin is interesting to test the method in different colour models, such as HSV and CMYK, as well as on non-normalized and color nor-malized images, in order to know the discriminative capability of the features on different conditions. Moreover, we expect to in-vestigate this approach by applying genetic algorithm or convolu-tional neural network in order to define the best associations and corresponding weights among the features. The method can also be expanded by applying both the Higuchi’s fractal dimension and different selection algorithms. Even more, we desired to apply the proposal herein to other types of images with the goal of analysing the robustness of the selected features.
    Author contribution statement
    Matheus Gonçalves Ribeiro developed the method and carried out the experiment; Leandro Alves Neves conceived and planned the method, as well as contributed to the writing and review; Marcelo Zanchetta do Nascimento presented critical feedback and helped define the research, analysis and manuscript; Guilherme Freire Roberto contributed to the experiments; Alessandro Santana Martins contributed to the experiments; Thaína Aparecida Azevedo Tosta contributed to the writing and review.
    Acknowledgements
    This study was financed in part by the Coordenao de Aper-fei oamento de Pessoal de Nvel Superior (CAPES) - Finance Code 33004153073P9, National Council for Scientific and Technological Development (CNPq) - Finance Code 427114/2016-0 and the Minas Gerais State Research Foundation (FAPEMIG) - Finance Code APQ-00578-18.
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