Texture analysis of sonographic image of placenta in pregnancies with normal and adverse outcomes, a pilot study.
Many maternal and fetal morbidity and mortality from complications of pregnancy have been attributed to placenta abnormality. Placenta assessment in developing countries is mainly through ultrasonography which is subjective and prone to error. Objective assessment of placental abnormalities through...
| Publicado en: | Radiography Vol. 29; no. 1; pp. 14 - 19 |
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| Autores principales: | , , , , |
| Formato: | research Journal Article |
| Publicado: |
W B Saunders
Jan2023
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=161324967&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 161324967 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 10788174 DPD jtl: Radiography issn: 10788174 maglogo: N pubinfo: dt: Jan2023 vid: 29 iid: 1 pid: 1351 pub: W B Saunders place: Philadelphia, Pennsylvania artinfo: ui: 161324967 161324967 161324967 10.1016/j.radi.2022.09.008 161324967 ppf: 14 ppct: 5 formats: tig: atl: Texture analysis of sonographic image of placenta in pregnancies with normal and adverse outcomes, a pilot study. aug: au: Abonyi, Obinna Everistus Idigo, Ugochinyere Felicitas Anakwue, Chukwunyelu Angel-Mary Agbo, Amechi Julius Ohagwu, Chukwuemeka Christopher affil: Department of Medical Radiography and Radiological Sciences, Faculty of Health Sciences and Technology. College of Medicine, University of Nigeria, Enugu Campus, Enugu State, Nigeria sug: subj: Ultrasonography, Prenatal Placenta Diseases Ultrasonography Placenta Anatomy and Histology Image Processing, Computer Assisted Methods Predictive Value of Tests Human Female Pregnancy Nigeria Prospective Studies Pilot Studies Placenta Pathology Algorithms Validity Female ab: Many maternal and fetal morbidity and mortality from complications of pregnancy have been attributed to placenta abnormality. Placenta assessment in developing countries is mainly through ultrasonography which is subjective and prone to error. Objective assessment of placental abnormalities through texture analysis has been frequently done using magnetic resonance images with little done on ultrasound generated images, thus, the need for this study. The study is aimed at using statistical texture analysis in characterizing placenta tissue into normal and abnormal placenta as well as testing the accuracy of different texture analysis algorithms in differentiating placenta into normal and abnormal placental tissues. This longitudinal study involved 500 ultrasound-generated placenta images from patients screened for adverse pregnancy outcomes in a private hospital in Enugu. These images were loaded onto an HP laptop for viewing. Two regions of interest were selected from the placenta tissue where texture features were extracted and were classified into normal and abnormal placentas using MaZda® software version 47 while the accuracy of the classification descriptors was assessed using WEKA classification algorithms. Co-occurrence matrix, run length matrix and histogram parameters differentiated normal placenta tissue from abnormal placental tissues (p-value <0.05) while variance is the only absolute gradient parameter that can differentiate normal placenta tissue from abnormal placenta tissues. All feature descriptors show high classification accuracy using KNN and ANN algorithms. Texture analysis can differentiate normal placenta tissues from abnormal placenta tissue which will reduce the errors associated with subjective assessment of the placenta echogenicity. Integrating these computer-aided algorithms into our ultrasound machines will lead to early detection of abnormal placenta tissues as early management results in better pregnancy outcomes. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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