• Resumo

    Towards a Complete Pipeline for Segmenting Nuclei in Feulgen-Stained Images

    Data de publicação: 04/09/2020

    ABSTRACT
    Cervical cancer is the second most common cancer type in women
    around the world. In some countries, due to non-existent or inadequate
    screening, it is often detected at late stages, making standard
    treatment options often absent or unaffordable. It is a deadly
    disease that could benefit from early detection approaches. It is
    usually done by cytological exams which consist of visually inspecting
    the nuclei searching for morphological alteration. Since it
    is done by humans, naturally, some subjectivity is introduced. Computational
    methods could be used to reduce this, where the first
    stage of the process would be the nuclei segmentation. In this context,
    we present a complete pipeline for the segmentation of nuclei
    in Feulgen-stained images using Convolutional Neural Networks.
    Here we show the entire process of segmentation, since the collection
    of the samples, passing through pre-processing, training the
    network, post-processing and results evaluation. We achieved an
    overall IoU of 0.78, showing the affordability of the approach of nuclei
    segmentation on Feulgen-stained images. The code is available
    in: https://github.com/luizbuschetto/feulgen_nuclei_segmentation

Anais do Computer on the Beach

O Computer on the Beach é um evento técnico-científico que visa reunir profissionais, pesquisadores e acadêmicos da área de Computação, a fim de discutir as tendências de pesquisa e mercado da computação em suas mais diversas áreas.

Access journal