{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T10:31:30Z","timestamp":1777890690664,"version":"3.51.4"},"reference-count":60,"publisher":"SAGE Publications","issue":"6","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["THC"],"published-print":{"date-parts":[[2020,11,17]]},"abstract":"<jats:p>BACKGROUD: Hydrocephalus is the most common anomaly of the fetal head characterized by an excessive accumulation of fluid in the brain processing. The diagnostic process of fetal heads using traditional evaluation techniques are generally time consuming and error prone. Usually, fetal head size is computed using an ultrasound (US) image around 20\u201322 weeks, which is the gestational age (GA). Biometrical measurements are extracted and compared with ground truth charts to identify normal or abnormal growth. METHODS: In this paper, an attempt has been made to enhance the Hydrocephalus characterization process by extracting other geometrical and textural features to design an efficient recognition system. The superiority of this work consists of the reduced time processing and the complexity of standard automatic approaches for routine examination. This proposed method requires practical insidiousness of the precocious discovery of fetuses\u2019 malformation to alert the experts about the existence of abnormal outcome. The first task is devoted to a proposed pre-processing model using a standard filtering and a segmentation scheme using a modified Hough transform (MHT) to detect the region of interest. Indeed, the obtained clinical parameters are presented to the principal component analysis (PCA) model in order to obtain a reduced number of measures which are employed in the classification stage. RESULTS: Thanks to the combination of geometrical and statistical features, the classification process provided an important ability and an interesting performance achieving more than 96% of accuracy to detect pathological subjects in premature ages. CONCLUSIONS: The experimental results illustrate the success and the accuracy of the proposed classification method for a factual diagnostic of fetal head malformation.<\/jats:p>","DOI":"10.3233\/thc-191752","type":"journal-article","created":{"date-parts":[[2020,3,17]],"date-time":"2020-03-17T15:18:49Z","timestamp":1584458329000},"page":"643-664","source":"Crossref","is-referenced-by-count":13,"title":["A computer-aided method based on geometrical texture features for a precocious detection of fetal Hydrocephalus in ultrasound images"],"prefix":"10.1177","volume":"28","author":[{"given":"Hanene","family":"Sahli","sequence":"first","affiliation":[{"name":"University of Tunis, ENSIT, LR13ES03 SIME, Tunis, Tunisia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Amine","family":"Ben Slama","sequence":"additional","affiliation":[{"name":"University of Tunis El Manar, ISTMT, LR13ES07, LRBTM, Tunis, Tunisia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aymen","family":"Mouelhi","sequence":"additional","affiliation":[{"name":"University of Tunis, ENSIT, LR13ES03 SIME, Tunis, Tunisia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nesrine","family":"Soayeh","sequence":"additional","affiliation":[{"name":"Obstetrics, Gynecology and Reproductive Department, Military Hospital, Tunis, Tunisia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Radhouane","family":"Rachdi","sequence":"additional","affiliation":[{"name":"Obstetrics, Gynecology and Reproductive Department, Military Hospital, Tunis, Tunisia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mounir","family":"Sayadi","sequence":"additional","affiliation":[{"name":"University of Tunis, ENSIT, LR13ES03 SIME, Tunis, Tunisia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","reference":[{"issue":"4","key":"10.3233\/THC-191752_ref1","doi-asserted-by":"crossref","first-page":"1268","DOI":"10.1016\/j.patcog.2007.09.006","article-title":"Detection of incomplete ellipse in images with strong noise by iterative randomized Hough transform (IRHT)","volume":"41","author":"Lu,","year":"2008","journal-title":"Pattern Recognition"},{"issue":"9","key":"10.3233\/THC-191752_ref2","doi-asserted-by":"crossref","first-page":"8","DOI":"10.5120\/2614-3646","article-title":"Speckle noise reduction of medical ultrasound images using Bayesshrink wavelet threshold","volume":"22","author":"Karthikeyan,","year":"2011","journal-title":"International Journal of Computer Applications"},{"key":"10.3233\/THC-191752_ref3","first-page":"830","article-title":"Reduction of periodic noise in Fourier domain optical coherence tomography images by frequency domain filtering","volume":"57","author":"Xie,","year":"2012","journal-title":"Biomedical Engineering\/Biomedizinische Technik"},{"key":"10.3233\/THC-191752_ref4","doi-asserted-by":"crossref","unstructured":"Lu, W., Tan, J., and Floyd, R.C. 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