Item request has been placed! ×
Item request cannot be made. ×
loading  Processing Request

Automatic image segmentation using Region-Based convolutional networks for Melanoma skin cancer detection ; Segmentación automática de imágenes mediante redes convolucionales basadas en regiones para la detección del cáncer de piel tipo melanoma

Item request has been placed! ×
Item request cannot be made. ×
loading   Processing Request
  • معلومة اضافية
    • بيانات النشر:
      Editorial Tecnológica de Costa Rica (entidad editora)
    • الموضوع:
      2022
    • Collection:
      Tecnológico de Costa Rica: Revistas del TEC
    • نبذة مختصرة :
      Melanoma is one of the most aggressive skin cancers, however, its early detection can significantly increase probabilities to cure it. Unfortunately, it is one of the most difficult skin cancers to detect, its detection relies mainly on the dermatologist’s expertise and experience with Melanoma. This research deals with targeting most of the common Melanoma stains or spots that could potentially evolve to Melanoma skin cancer. Region-based Convolutional Neural Networks were used as the model to detect and segment images of the skin area of interest. The neural network model is focused on providing instance segmentation rather than only a boxbounding object detection. The Mask R-CNN model was implemented to provide a solution for small trained datasets scenarios. Two pipelines were implemented, the first one was with only the Region-Based Convolutional Neural Network and the other one was a combined pipeline with a first stage using Mask R-CNN and then getting the result to use as feedback in a second stage implementing Grabcut, which is another segmentation method based on graphic cuts. Results demonstrated through Dice Similarity Coefficient and Jaccard Index that Mask R-CNN alone performed better in proper segmentation than Mask R-CNN + Grabcut model. In both models’ results, variation was very small when the training dataset size changed between 160, 100, and 50 images. In both of the pipelines, the models were capable of running the segmentation correctly, which illustrates that focalization of the zone is possible with very small datasets and the potential use of automatic segmentation to assist in Melanoma detection. ; El Melanoma es uno de los cánceres de piel más agresivos, sin embargo, su diagnóstico en una etapa temprana aumenta significativamente las opciones y el éxito en el tratamiento. Desafortunadamente, el Melanoma es uno de los cánceres de piel más difíciles de detectar, pues depende principalmente de la pericia y experiencia del dermatólogo. Esta investigación se enfoca en las manchas comunes ...
    • File Description:
      application/pdf
    • Relation:
      https://revistas.tec.ac.cr/index.php/tec_marcha/article/view/6479/6293; https://revistas.tec.ac.cr/index.php/tec_marcha/article/view/6479
    • الرقم المعرف:
      10.18845/tm.v35i9.6479
    • الدخول الالكتروني :
      https://revistas.tec.ac.cr/index.php/tec_marcha/article/view/6479
      https://doi.org/10.18845/tm.v35i9.6479
    • Rights:
      https://creativecommons.org/licenses/by-nc-nd/4.0
    • الرقم المعرف:
      edsbas.934E4F1F