Segmentation and classification of ovarian cancer based on conditional adversarial image to image translation approach

A Kodipalli, S Devi, S Dasar, T Ismail - Expert Systems, 2022 - Wiley Online Library
Medical image analysis and disease diagnosis have significantly improved with the use of AI
and Machine Learning algorithms. Automated systems for medical image analysis will help …

[HTML][HTML] Swin transformer and deep convolutional neural networks for coastal wetland classification using sentinel-1, sentinel-2, and LiDAR data

A Jamali, M Mahdianpari - Remote Sensing, 2022 - mdpi.com
The use of machine learning algorithms to classify complex landscapes has been
revolutionized by the introduction of deep learning techniques, particularly in remote …

Pconet: A convolutional neural network architecture to detect polycystic ovary syndrome (pcos) from ovarian ultrasound images

AKMS Hosain, MHK Mehedi… - … on Engineering and …, 2022 - ieeexplore.ieee.org
Polycystic Ovary Syndrome (PCOS) is an endrocrinological dysfunction prevalent among
women of reproductive age. PCOS is a combination of syndromes caused by an excess of …

A deep learning fusion approach to diagnosis the polycystic ovary syndrome (pcos)

A Alamoudi, IU Khan, N Aslam… - … Intelligence and Soft …, 2023 - Wiley Online Library
One of the leading causes of female infertility is PCOS, which is a hormonal disorder
affecting women of childbearing age. The common symptoms of PCOS include increased …

Segmentation of ovarian cancer using active contour and random walker algorithm

PJ Ruchitha, YS Richitha, A Kodipalli… - 2021 5th International …, 2021 - ieeexplore.ieee.org
Image Processing nowadays has been commonly used in different medical fields and
includes many types of techniques such as storage, communication, presentation …

[HTML][HTML] Application of deep convolutional neural networks for discriminating benign, borderline, and malignant serous ovarian tumors from ultrasound images

H Wang, C Liu, Z Zhao, C Zhang, X Wang, H Li… - Frontiers in …, 2021 - frontiersin.org
Objective This study aimed to evaluate the performance of the deep convolutional neural
network (DCNN) to discriminate between benign, borderline, and malignant serous ovarian …

[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 Comprehensive Study on Deep Learning Models for the Detection of Ovarian Cancer and Glomerular Kidney Disease using Histopathological Images

SJKJ Kumar, GP Kanna, DP Raja, Y Kumar - Archives of Computational …, 2024 - Springer
Ovarian cancer is a significant health concern because of its high mortality rates and
potential to cause glomerular injury, which can obstruct the urinary tract. It is very crucial to …

Detecting malignancy of ovarian tumour using convolutional neural network: A review

M Mathur, V Jindal, G Wadhwa - 2020 Sixth International …, 2020 - ieeexplore.ieee.org
Ovaries are important part of female reproductive system. The importance of these tiny
glands is derived from the production of female sex hormones and female gametes. The …

Feature‐versus deep learning‐based approaches for the automated detection of brain tumor with magnetic resonance images: A comparative study

U Raghavendra, A Gudigar, TN Rao… - … Journal of Imaging …, 2022 - Wiley Online Library
The public health is significantly affected by development of brain tumors in human patients.
Glioblastoma (GBM) is a relatively common, malignant form of brain tumor, which is currently …