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 …

[PDF][PDF] Performance Analysis of Segmentation and Classification of CT-Scanned Ovarian Tumours Using U-Net and Deep Convolutional Neural Networks. Diagnostics …

A Kodipalli, SL Fernandes, V Gururaj… - doi. org/10.3390 …, 2023 - academia.edu
Difficulty in detecting tumours in early stages is the major cause of mortalities in patients,
despite the advancements in treatment and research regarding ovarian cancer. Deep …

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 …

[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 …

Ovarian Tumors Detection and Classification on Ultrasound Images Using One-stage Convolutional Neural Networks

VH Le, TL Pham - Journal of Robotics and Control (JRC), 2024 - journal.umy.ac.id
Currently, the advent of CNN (Convolutional Neural Network) has brought very convincing
results to computer vision problems. One-stage CNNs are a suitable choice for research and …

[HTML][HTML] Performance Analysis of Segmentation and Classification of CT-Scanned Ovarian Tumours Using U-Net and Deep Convolutional Neural Networks

A Kodipalli, SL Fernandes, V Gururaj… - Diagnostics, 2023 - mdpi.com
Difficulty in detecting tumours in early stages is the major cause of mortalities in patients,
despite the advancements in treatment and research regarding ovarian cancer. Deep …

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 …

An improved YOLOv3 model for detecting location information of ovarian cancer from CT images

X Wang, H Li, L Wang, Y Yu, H Zhou… - Intelligent Data …, 2021 - content.iospress.com
Ovarian cancer is a malignant tumor that poses a serious threat to women's lives. Computer-
aided diagnosis (CAD) systems can classify the type of ovarian tumors, but few of them can …

TLOD: Innovative ovarian tumor detection for accurate multiclass classification and clinical application

MJ Sundari, NC Brintha - Network Modeling Analysis in Health Informatics …, 2024 - Springer
Ovarian tumors pose a major threat to women's health, mostly remaining undetected until
they reach advanced stages, resulting in complex treatment and decreased survival rates …

[PDF][PDF] Ovarian Tumors Detection and Classification from Ultrasound Images Based on YOLOv8

TL Pham, VH Le - Journal of Advances in Information Technology, 2024 - jait.us
Ovarian cancer is the 7th most common malignant tumor and the 8th leading cause of death
in women. Therefore, ovarian cancer detection early and on the image data as ultrasound …