RGB Channel Superposition Algorithm with Acetowhite Mask Images in a Cervical Cancer Classification Deep Learning Model
Cervical cancer is one of the main causes of death from cancer in women. However, it can be treated successfully at an early stage. This study aims to propose an image processing algorithm based on acetowhite, which is an important criterion for diagnosing cervical cancer, to increase the accuracy o...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-05-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/22/9/3564 |
| _version_ | 1797502710069592064 |
|---|---|
| author | Yoon Ji Kim Woong Ju Kye Hyun Nam Soo Nyung Kim Young Jae Kim Kwang Gi Kim |
| author_facet | Yoon Ji Kim Woong Ju Kye Hyun Nam Soo Nyung Kim Young Jae Kim Kwang Gi Kim |
| author_sort | Yoon Ji Kim |
| collection | DOAJ |
| description | Cervical cancer is one of the main causes of death from cancer in women. However, it can be treated successfully at an early stage. This study aims to propose an image processing algorithm based on acetowhite, which is an important criterion for diagnosing cervical cancer, to increase the accuracy of the deep learning classification model. Then, we mainly compared the performance of the model, the original image without image processing, a mask image made with acetowhite as the region of interest, and an image using the proposed algorithm. In conclusion, the deep learning classification model based on images with the proposed algorithm achieved an accuracy of 81.31%, which is approximately 9% higher than the model with original images and approximately 4% higher than the model with acetowhite mask images. Our study suggests that the proposed algorithm based on acetowhite could have a better performance than other image processing algorithms for classifying stages of cervical images. |
| first_indexed | 2024-03-10T03:39:59Z |
| format | Article |
| id | doaj.art-52104f1769a845f796aeb0d7f91bff91 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T03:39:59Z |
| publishDate | 2022-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-52104f1769a845f796aeb0d7f91bff912023-11-23T09:20:18ZengMDPI AGSensors1424-82202022-05-01229356410.3390/s22093564RGB Channel Superposition Algorithm with Acetowhite Mask Images in a Cervical Cancer Classification Deep Learning ModelYoon Ji Kim0Woong Ju1Kye Hyun Nam2Soo Nyung Kim3Young Jae Kim4Kwang Gi Kim5Department of Biomedical Engineering, Gil Medical Center, College of Medicine, Gachon University, 21 Namdong-daero 774 Beon-gil, Namdong-gu, Incheon 21565, KoreaDepartment of Obstetrics & Gynecology, Seoul Hospital, Ewha Womans University, Seoul 07804, KoreaDepartment of Obstetrics & Gynecology, Bucheon Hospital, Soonchunhyang University, Bucheon-si 14584, KoreaR & D Center, NTL Medical Institute, Seongnam-si 13449, KoreaDepartment of Biomedical Engineering, Gil Medical Center, College of Medicine, Gachon University, 21 Namdong-daero 774 Beon-gil, Namdong-gu, Incheon 21565, KoreaDepartment of Biomedical Engineering, Gil Medical Center, College of Medicine, Gachon University, 21 Namdong-daero 774 Beon-gil, Namdong-gu, Incheon 21565, KoreaCervical cancer is one of the main causes of death from cancer in women. However, it can be treated successfully at an early stage. This study aims to propose an image processing algorithm based on acetowhite, which is an important criterion for diagnosing cervical cancer, to increase the accuracy of the deep learning classification model. Then, we mainly compared the performance of the model, the original image without image processing, a mask image made with acetowhite as the region of interest, and an image using the proposed algorithm. In conclusion, the deep learning classification model based on images with the proposed algorithm achieved an accuracy of 81.31%, which is approximately 9% higher than the model with original images and approximately 4% higher than the model with acetowhite mask images. Our study suggests that the proposed algorithm based on acetowhite could have a better performance than other image processing algorithms for classifying stages of cervical images.https://www.mdpi.com/1424-8220/22/9/3564cervical canceracetowhiteRGB channel superpositiondeep learningResNet |
| spellingShingle | Yoon Ji Kim Woong Ju Kye Hyun Nam Soo Nyung Kim Young Jae Kim Kwang Gi Kim RGB Channel Superposition Algorithm with Acetowhite Mask Images in a Cervical Cancer Classification Deep Learning Model Sensors cervical cancer acetowhite RGB channel superposition deep learning ResNet |
| title | RGB Channel Superposition Algorithm with Acetowhite Mask Images in a Cervical Cancer Classification Deep Learning Model |
| title_full | RGB Channel Superposition Algorithm with Acetowhite Mask Images in a Cervical Cancer Classification Deep Learning Model |
| title_fullStr | RGB Channel Superposition Algorithm with Acetowhite Mask Images in a Cervical Cancer Classification Deep Learning Model |
| title_full_unstemmed | RGB Channel Superposition Algorithm with Acetowhite Mask Images in a Cervical Cancer Classification Deep Learning Model |
| title_short | RGB Channel Superposition Algorithm with Acetowhite Mask Images in a Cervical Cancer Classification Deep Learning Model |
| title_sort | rgb channel superposition algorithm with acetowhite mask images in a cervical cancer classification deep learning model |
| topic | cervical cancer acetowhite RGB channel superposition deep learning ResNet |
| url | https://www.mdpi.com/1424-8220/22/9/3564 |
| work_keys_str_mv | AT yoonjikim rgbchannelsuperpositionalgorithmwithacetowhitemaskimagesinacervicalcancerclassificationdeeplearningmodel AT woongju rgbchannelsuperpositionalgorithmwithacetowhitemaskimagesinacervicalcancerclassificationdeeplearningmodel AT kyehyunnam rgbchannelsuperpositionalgorithmwithacetowhitemaskimagesinacervicalcancerclassificationdeeplearningmodel AT soonyungkim rgbchannelsuperpositionalgorithmwithacetowhitemaskimagesinacervicalcancerclassificationdeeplearningmodel AT youngjaekim rgbchannelsuperpositionalgorithmwithacetowhitemaskimagesinacervicalcancerclassificationdeeplearningmodel AT kwanggikim rgbchannelsuperpositionalgorithmwithacetowhitemaskimagesinacervicalcancerclassificationdeeplearningmodel |