Amniotic fluid segmentation based on pixel classification using local window information and distance angle pixel-Reference-Cited by-同舟云学术

Amniotic fluid segmentation based on pixel classification using local window information and distance angle pixel

Published:2021-08 Issue: Volume:107 Page:107196
ISSN:1568-4946
Container-title:Applied Soft Computing
language:en
Short-container-title:Applied Soft Computing

Author:

Ayu Putu Desiana Wulaning^ORCID,Hartati Sri,Musdholifah Aina,Nurdiati Detty S.

Funder

Universitas Gadjah Mada

Publisher

Elsevier BV

Subject

Software

Reference69 articles.

1. Amniotic fluid deficiency and congenital abnormalities both influence fluctuating asymmetry in developing limbs of human deceased fetuses;Ten Broek;J. PLoS ONE,2013

2. Potential function of amniotic fluid in fetal development-novel insights by comparing the composition of human amniotic fluid with umbilical cord and maternal serum at mid and late gestation;Tong;J. Chinese Med. Assoc.,2009

3. Amniotic fluid index versus single deepest vertical pocket: a meta-analysis of randomized controlled trials;Nabhan;J. Gynecol. Obstet.,2009

4. Amniotic fluid volume assessment using the single deepest pocket technique in bangladesh;Rashid;J. Med. Ultrasound.,2013

5. Fetal imaging;Martínez-León;J. Ultrasound Med.,2014

Cited by 7 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. U-Net Tuning Hyperparameter for Segmentation in Amniotic Fluid Ultrasonography Image;2022 4th International Conference on Cybernetics and Intelligent System (ICORIS);2022-10-08

2. Deep Learning-Based Computer-Aided Classification of Amniotic Fluid Using Ultrasound Images from Saudi Arabia;Big Data and Cognitive Computing;2022-10-03

3. Amniotic Fluid Classification and Artificial Intelligence: Challenges and Opportunities;Sensors;2022-06-17

4. Breast microscopic cancer segmentation and classification using unique 4‐qubit ‐quantum model;Microscopy Research and Technique;2022-01-18

5. Machine learning model for umbilical cord classification using combination coiling index and texture feature based on 2-D Doppler ultrasound images;Health Informatics Journal;2022-01