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 …
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 …
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 …
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)
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 …
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 …
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 …
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 …
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
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 …
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
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 …
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
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 …
Glioblastoma (GBM) is a relatively common, malignant form of brain tumor, which is currently …