Mask region-based CNNs for cervical cancer progression diagnosis on pap smear examinations
This research presents a novel approach for cervical cancer detection and segmentation using tissue images with multiple cells. The study employs a novel deep learning architecture based on Mask Region-Based Convolutional Neural Network (RCNN) and statistical analysis. This new architecture enables...
Main Authors: | Carolina Rutili de Lima, Said G. Khan, Syed H. Shah, Luthiari Ferri |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2023-11-01
|
Series: | Heliyon |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844023085961 |
Similar Items
-
Detection of Cervix Cancer from Pap-smear Images
by: Fatma Betül Akyol, et al.
Published: (2020-08-01) -
CLASSIFICATION OF CERVICAL CANCER CELLS IN PAP SMEAR SCREENING TEST
by: S. Athinarayanan, et al.
Published: (2016-05-01) -
COMPUTER AIDED DIAGNOSIS FOR DETECTION AND STAGE IDENTIFICATION OF CERVICAL CANCER BY USING PAP SMEAR SCREENING TEST IMAGES
by: S. Athinarayanan, et al.
Published: (2016-05-01) -
Diagnosis of Cervical Cancer Using Texture and Morphological Features in Pap Smear Images
by: Hamid Hosseinabadi, et al.
Published: (2020-09-01) -
A Crop Image Segmentation and Extraction Algorithm Based on Mask RCNN
by: Shijie Wang, et al.
Published: (2021-09-01)