Automated adenocarcinoma lung cancer tissue images segmentation based on clustering
Cancer is one of the main dead causes worldwide. It is re- sponsible for an approximate of 1 out of 6 deaths globally and lung cancer is along breast cancer, the most common types of cancer in the population, which confirms the importance of studies associated with it. This work presents an approac...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Instituto Tecnológico de Costa Rica
2022-11-01
|
| Series: | Tecnología en Marcha |
| Subjects: | |
| Online Access: | https://172.20.14.50/index.php/tec_marcha/article/view/6442 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849412603588116480 |
|---|---|
| author | Bryan Cervantes-Ramirez Francisco Siles |
| author_facet | Bryan Cervantes-Ramirez Francisco Siles |
| author_sort | Bryan Cervantes-Ramirez |
| collection | DOAJ |
| description |
Cancer is one of the main dead causes worldwide. It is re- sponsible for an approximate of 1 out of 6 deaths globally and lung cancer is along breast cancer, the most common types of cancer in the population, which confirms the importance of studies associated with it. This work presents an approach toward lung cancer histological tissue images segmentation based on colour. The proposed method for the segmentation is K-means clustering, providing promising results that may become as an assistance for pathologists, as it can help them reduce the time consumed reviewing the slides and giving a more objective perspective in order to provide a diagnose and specific treatment.
|
| format | Article |
| id | doaj-art-64156a027ea94b99a2ae4521d47c552c |
| institution | Kabale University |
| issn | 0379-3982 2215-3241 |
| language | English |
| publishDate | 2022-11-01 |
| publisher | Instituto Tecnológico de Costa Rica |
| record_format | Article |
| series | Tecnología en Marcha |
| spelling | doaj-art-64156a027ea94b99a2ae4521d47c552c2025-08-20T03:34:24ZengInstituto Tecnológico de Costa RicaTecnología en Marcha0379-39822215-32412022-11-0135810.18845/tm.v35i8.6442Automated adenocarcinoma lung cancer tissue images segmentation based on clusteringBryan Cervantes-RamirezFrancisco Siles Cancer is one of the main dead causes worldwide. It is re- sponsible for an approximate of 1 out of 6 deaths globally and lung cancer is along breast cancer, the most common types of cancer in the population, which confirms the importance of studies associated with it. This work presents an approach toward lung cancer histological tissue images segmentation based on colour. The proposed method for the segmentation is K-means clustering, providing promising results that may become as an assistance for pathologists, as it can help them reduce the time consumed reviewing the slides and giving a more objective perspective in order to provide a diagnose and specific treatment. https://172.20.14.50/index.php/tec_marcha/article/view/6442Digital pathologypattern recognitionlung cancer |
| spellingShingle | Bryan Cervantes-Ramirez Francisco Siles Automated adenocarcinoma lung cancer tissue images segmentation based on clustering Tecnología en Marcha Digital pathology pattern recognition lung cancer |
| title | Automated adenocarcinoma lung cancer tissue images segmentation based on clustering |
| title_full | Automated adenocarcinoma lung cancer tissue images segmentation based on clustering |
| title_fullStr | Automated adenocarcinoma lung cancer tissue images segmentation based on clustering |
| title_full_unstemmed | Automated adenocarcinoma lung cancer tissue images segmentation based on clustering |
| title_short | Automated adenocarcinoma lung cancer tissue images segmentation based on clustering |
| title_sort | automated adenocarcinoma lung cancer tissue images segmentation based on clustering |
| topic | Digital pathology pattern recognition lung cancer |
| url | https://172.20.14.50/index.php/tec_marcha/article/view/6442 |
| work_keys_str_mv | AT bryancervantesramirez automatedadenocarcinomalungcancertissueimagessegmentationbasedonclustering AT franciscosiles automatedadenocarcinomalungcancertissueimagessegmentationbasedonclustering |