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 …

Deep Learning for Comparative Study of Ovarian Cancer Detection on Histopathological Images

WO Falana, A Serener, S Serte - 2023 7th International …, 2023 - ieeexplore.ieee.org
Ovarian cancer is a serious threat to women's health. It comes from the ovaries, which are
important for producing eggs and hormones, such as estrogen and progesterone. Ovarian …

Enhancing Ovarian Cancer Detection: A Deep Learning Approach with MobileNetV3 and ResNet50

CV Kwatra, H Kaur - 2023 Seventh International Conference …, 2023 - ieeexplore.ieee.org
Ovarian cancer, commonly known as the “silent killer,” presents notable obstacles in terms of
timely detection and management. This work aims to explore the capabilities of deep …

A comparative study of various machine learning methods on ovarian tumor

MJ Sundari, NC Brintha - 2021 Sixth International Conference …, 2021 - ieeexplore.ieee.org
Ovarian tumor is a kind of cancer which is commonly encountered in females. It is critical to
accurately anticipate the development of Benign Ovarian Tumors (BOT) cancers. This …

Automated detection of Malignant Lesions in the ovary using deep learning models and XAI

MHS Ifty, N Nirjan, MA Diganta, L Islam, RA Ornate - 2024 - dspace.bracu.ac.bd
Cancer is a complex and highly invasive disease that forms due to the abnormal growth of
cells in any part of the body. A majority of cancers are unraveled and treated by …

A convolutional neural network approach for detecting malignancy of ovarian cancer

M Mathur, V Jindal - Soft Computing and Signal Processing: Proceedings …, 2022 - Springer
Ovarian malignant growth has a poor endurance rate because general analysis and
improved techniques are required for its initial discovery. Ovarian malignancy is the sixth …

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 …

[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 …

Systematic analysis of ovarian cancer empowered with machine and deep learning: a taxonomy and future challenges

R Sajjad, MF Khan, A Nawaz, MT Ali, M Adil - Journal of Computing & …, 2022 - jcbi.org
Abstract Machine and Deep learning has witnessed an exceptional amount of admiration in
recent years. ML has ability to learn data itself by predicting uncertain conditions or future …

An Empirical Evaluation of a Novel Ensemble Deep Neural Network Model and Explainable AI for Accurate Segmentation and Classification of Ovarian Tumors Using …

A Kodipalli, SL Fernandes, S Dasar - Diagnostics, 2024 - mdpi.com
Ovarian cancer is one of the leading causes of death worldwide among the female
population. Early diagnosis is crucial for patient treatment. In this work, our main objective is …