[Retracted] Automatic Detection and Segmentation of Ovarian Cancer Using a Multitask Model in Pelvic CT Images

X Wang, H Li, P Zheng - Oxidative Medicine And Cellular …, 2022 - Wiley Online Library
Ovarian cancer is one of the most common malignant tumours of female reproductive organs
in the world. The pelvic CT scan is a common examination method used for the screening of …

A hybrid deep learning approach for detection and segmentation of ovarian tumours

HH Maria, AM Jossy, S Malarvizhi - Neural Computing and Applications, 2023 - Springer
In recent days, artificial intelligence (AI) is gaining worldwide popularity in several industries
among which healthcare is an important sector. AI is being used in healthcare to reduce …

Automatic classification of ovarian cancer types from cytological images using deep convolutional neural networks

M Wu, C Yan, H Liu, Q Liu - Bioscience reports, 2018 - portlandpress.com
Ovarian cancer is one of the most common gynecologic malignancies. Accurate
classification of ovarian cancer types (serous carcinoma, mucous carcinoma, endometrioid …

Ovarian cancer detection in computed tomography images using ensembled deep optimized learning classifier

A Boyanapalli, A Shanthini - Concurrency and Computation …, 2023 - Wiley Online Library
Ovarian cancer (OC) is one of the most common deadly diseases threatening women
worldwide. In day to day life, a challenging task still exists for identifying OC in the early …

[HTML][HTML] Deep learning in ovarian cancer diagnosis: a comprehensive review of various imaging modalities

MH Sadeghi, S Sina, H Omidi… - Polish Journal of …, 2024 - ncbi.nlm.nih.gov
Ovarian cancer poses a major worldwide health issue, marked by high death rates and a
deficiency in reliable diagnostic methods. The precise and prompt detection of ovarian …

An inception‐ResNet deep learning approach to classify tumours in the ovary as benign and malignant

A Kodipalli, S Guha, S Dasar, T Ismail - Expert Systems, 2022 - Wiley Online Library
The classification of tumours into benign and malignant continues to date to be a very
relevant and significant research topic in the cancer research domain. With the advent of …

Deep yolo-based detection of breast cancer mitotic-cells in histopathological images

MM Al Zorgani, I Mehmood, H Ugail - Proceedings of 2021 International …, 2022 - Springer
Coinciding with advances in whole-slide imaging scanners, it is become essential to
automate the conventional image-processing techniques to assist pathologists with some …

YOLO V3 and YOLO V4 for masses detection in mammograms with resnet and inception for masses classification

GH Aly, MAER Marey, S El-Sayed Amin… - … : Proceedings of AMLTA …, 2021 - Springer
Breast cancer is considered the most common type of cancer in women. It is the second
leading cause of death all over the world among women. However, the process of mass …

Deep learning for the ovarian lesion localization and discrimination between borderline and malignant ovarian tumors based on routine MR imaging

Y Wang, H Zhang, T Wang, L Yao, G Zhang, X Liu… - Scientific Reports, 2023 - nature.com
To establish a deep learning (DL) model in differentiating borderline ovarian tumor (BOT)
from epithelial ovarian cancer (EOC) on conventional MR imaging. We retrospectively …

An improved method of polyp detection using custom YOLOv4-tiny

M Doniyorjon, R Madinakhon, M Shakhnoza, YI Cho - Applied Sciences, 2022 - mdpi.com
Automatic detection of Wireless Endoscopic Images can avoid dangerous possible diseases
such as cancers. Therefore, a number of articles have been published on different methods …