<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.3 20210610//EN" "JATS-journalpublishing1-3.dtd">
<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="en"><front><journal-meta><journal-id journal-id-type="publisher-id">urovest</journal-id><journal-title-group><journal-title xml:lang="en">Urology Herald</journal-title><trans-title-group xml:lang="ru"><trans-title>Вестник урологии</trans-title></trans-title-group></journal-title-group><issn pub-type="epub">2308-6424</issn><publisher><publisher-name>Rostov State Medical University</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.21886/2308-6424-2021-9-3-19-24</article-id><article-id custom-type="elpub" pub-id-type="custom">urovest-468</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>ORIGINAL ARTICLES</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>ОРИГИНАЛЬНЫЕ СТАТЬИ</subject></subj-group></article-categories><title-group><article-title>The three-dimensional reconstruction of the dilated renal pelvicalyceal system by non-enhanced computed tomography</article-title><trans-title-group xml:lang="ru"><trans-title>Трёхмерная реконструкция расширенной полостной системы почки по нативной компьютерной томографии</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-2359-6973</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Гулиев</surname><given-names>Б. Г.</given-names></name><name name-style="western" xml:lang="en"><surname>Guliev</surname><given-names>B. G.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Бахман Гидаятович Гулиев – д.м.н., профессор; профессор кафедры урологии ФГБОУ ВО СЗГМУ им. И. И. Мечникова Минздрава России; руководитель центра урологии с робот-ассистированной хирургией Мариинской больницы</p><p>191015, г. Санкт-Петербург, ул. Кирочная, д. 41</p><p>191014, г. Санкт-Петербург, пр-т Литейный, д. 56</p><p>тел.: +7 (921) 945-34-80</p></bio><bio xml:lang="en"><p>Bakhman G. Guliev – M.D., Dr. Sc. (M), Full Prof.; Prof., Dept. of Urology, Mechnikov North-West State Medical University; Head, Urology Centre with Robot-assisted Surgery</p><p>191015, St. Petersburg, 41 Kirochnaya st.</p><p>191014, St. Petersburg, 56 Liteiny ave.</p><p>tel.: +7 (921) 945-34-80</p></bio><email xlink:type="simple">gulievbg@mail.ru191015</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-8606-9791</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Комяков</surname><given-names>Б. К.</given-names></name><name name-style="western" xml:lang="en"><surname>Komyakov</surname><given-names>B. K.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Борис Кириллович Комяков – д.м.н., профессор; заведующий кафедрой урологии</p><p>191015, г. Санкт-Петербург, ул. Кирочная, д. 41</p></bio><bio xml:lang="en"><p>Boris K. Komyakov – M.D., Dr. Sc. (M), Full Prof.; Head, Dept. of Urology</p><p>191015, St. Petersburg, 41 Kirochnaya st.</p></bio><email xlink:type="simple">komyakovbk@mail.ru</email><xref ref-type="aff" rid="aff-2"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-3521-8937</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Талышинский</surname><given-names>А. Э.</given-names></name><name name-style="western" xml:lang="en"><surname>Talyshinskiy</surname><given-names>A. E.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Талышинский Али Эльманович – клинический ординатор кафедры урологии</p><p>191015, г. Санкт-Петербург, ул. Кирочная, д. 41</p></bio><bio xml:lang="en"><p>Ali E. Talyshinskiy – Postgraduate student; Dept. of Urology</p><p>191015, St. Petersburg, 41 Kirochnaya st.</p></bio><email xlink:type="simple">ali-ma@mail.ru</email><xref ref-type="aff" rid="aff-2"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>ФГБОУ ВО «Северо-Западный государственный медицинский университет им. И. И. Мечникова» Минздрава России; Центр урологии с робот-ассистированной хирургией Мариинской больницы</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Mechnikov North-Western State Medical University; Urology Centre with Robot-assisted Surgery, St. Petersburg Mariinsky Hospital</institution><country>Russian Federation</country></aff></aff-alternatives><aff-alternatives id="aff-2"><aff xml:lang="ru"><institution>ФГБОУ ВО «Северо-Западный государственный медицинский университет им. И. И. Мечникова» Минздрава России</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Mechnikov North-Western State Medical University</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2021</year></pub-date><pub-date pub-type="epub"><day>04</day><month>10</month><year>2021</year></pub-date><volume>9</volume><issue>3</issue><fpage>19</fpage><lpage>24</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Guliev B.G., Komyakov B.K., Talyshinskiy A.E., 2021</copyright-statement><copyright-year>2021</copyright-year><copyright-holder xml:lang="ru">Гулиев Б.Г., Комяков Б.К., Талышинский А.Э.</copyright-holder><copyright-holder xml:lang="en">Guliev B.G., Komyakov B.K., Talyshinskiy A.E.</copyright-holder><license license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://www.urovest.ru/jour/article/view/468">https://www.urovest.ru/jour/article/view/468</self-uri><abstract><sec><title>Introduction</title><p>Introduction. The three-dimensional reconstruction of the renal pelvicalyceal system (PCS) is possible when performing enhanced computed tomography (CT). However, the use of a contrast agent has its limitations associated with the presence of allergy and chronic kidney disease.</p></sec><sec><title>Purpose of the study</title><p>Purpose of the study. To describe the method of semi-autonomous three-dimensional (3D) reconstruction of the PCS based on non-enhanced CT images of patients with upper urinary tract obstruction.</p></sec><sec><title>Materials and methods</title><p>Materials and methods. Five patients diagnosed with renal colic were recruited from April-May 2021. All patients underwent CT-urography after informed consent. Medical Imaging Interaction Toolkit program (MITK) expanded with explainable update were used for 3D-reconstruction of PCS via excretory and native phases. To assess the accuracy of the latter, both contrast and non-contrast models were compared regarding their surface area. Also, the PCS of one patient was used to reconstruct virtual endoscopic views based on enhanced and non-enhanced models. Five urologists estimated their similarity and potential use of non-enhanced models for the interventional planning via a Likert scale questionnaire. The resulting models were also analyzed by programmer-engineers to test their suitability for 3D-printing.</p></sec><sec><title>Results</title><p>Results. The average surface area of enhanced and non-enhanced models was 3291 mm2 and 2879 mm2, respectively. Obtained models were suitable for their intraluminal reconstruction and potential 3D-printing. Analyzed properties of non-enhanced models were estimated at 4.5 out of 5.0.</p></sec><sec><title>Conclusion</title><p>Conclusion. The described semi-autonomous reconstruction of the renal PCS based on non-enhanced CT images allows for a short time to reconstruct its 3D-view in patients with the upper urinary tract obstruction.</p></sec></abstract><trans-abstract xml:lang="ru"><sec><title>Введение</title><p>Введение. Трёхмерная реконструкция чашечно-лоханочной системы (ЧЛС) почки возможна при проведении компьютерной томографии (КТ) с урографией. Однако использование контрастного вещества имеет свои ограничения, такие как аллергия на препарат и хроническая болезнь почек (ХБП).</p></sec><sec><title>Цель исследования</title><p>Цель исследования. Описание методики полуавтономного выделения ЧЛС на изображениях нативной КТ с её последующей 3D-реконструкцией при обструкции верхних мочевых путей (ВМП).</p></sec><sec><title>Материалы и методы</title><p>Материалы и методы. С апреля 2021 по май 2021 года было отобрано 5 пациентов с диагнозом почечная колика, которым выполняли КТ-урографию. Далее с помощью программы Medical Imaging Interaction Toolkit (MITK) и дополнительного алгоритма вручную на каждом нативном срезе отмечали три точки в пределах ЧЛС для определения её границ и построения 3D-модели. Для оценки точности реконструкции проводили сравнение объёма получаемых виртуальных моделей с объёмом контрастной реконструкции. Пять урологов оценивали информативность таких реконструкций для изучения анатомии ЧЛС конкретного пациента. Полученные модели были также проанализированы программистами для пригодности к 3D-печати.</p></sec><sec><title>Результаты</title><p>Результаты. Средняя площадь поверхности контрастных и бесконтрастных моделей составила 3291 мм2 и 2879 мм2. При сравнении контрастных и бесконтрастных 3D моделей, а также оценке последних для предоперационного планирования и их рентабельности средний балл урологов составил 4,5 из 5,0. Инженеры подтвердили пригодность бесконтрастных моделей для их трёхмерной печати.</p></sec><sec><title>Выводы</title><p>Выводы. Описанная полуавтономная реконструкция полостной системы почки по бесконтрастным КТ-снимкам позволяет за короткий промежуток времени реконструировать её 3D-вид у пациентов с обструкцией ВМП.</p></sec></trans-abstract><kwd-group xml:lang="ru"><kwd>почка</kwd><kwd>трёхмерная реконструкция</kwd><kwd>полость почки</kwd><kwd>нативная КТ</kwd></kwd-group><kwd-group xml:lang="en"><kwd>kidney</kwd><kwd>3D-reconstruction</kwd><kwd>pelvicalyceal system</kwd><kwd>non-enhanced CT</kwd></kwd-group></article-meta></front><body><sec><title>Introduction</title><p>Presently, non-enhanced computed tomography (CT) is a standard method of diagnostics of nephroureterolithiasis that provides preoperative visualization of the localization, density, and size of stone [<xref ref-type="bibr" rid="cit1">1</xref>]. However, its significant drawback is the impossibility of a 3D-visualization of the pelvicalyceal system (PCS). A detailed study of the peculiarities of PCS structure (number and orientation of calyces, length and width of their necks, and an angle ratio of different parts) is required for the choice of optimal surgical tactics. Along with that, this data can be obtained by CT with intravenous contrast that allows for 3D-reconstruction before the surgery. However, this increases radiation exposure on the patient. Besides, a contrast agent is contraindicated in patients with Chronic Kidney Disease (CKD) and hypersensitivity to the drug [<xref ref-type="bibr" rid="cit2">2</xref>]. The above-mentioned drawbacks require the development of 3D-reconstruction methods of PCS reconstruction based on contactless CT. There are scientific publications that describe methods of 3D reconstruction of renal structures by non-enhanced CT images but they target the visualization of its parenchyma [3, 4]. Only one article was dedicated to the reconstruction of PCS [<xref ref-type="bibr" rid="cit5">5</xref>]. Besides, the isolation of the borders of the renal cavity system was made manually, which significantly elongated the time of preparation of the data and limited the application of this method into clinical practice.</p><p>Thus, the present study aimed to describe a method of semiautomated isolation of PCS in the images of non-enhanced CT with further 3D-reconstruction.</p></sec><sec><title>Materials and methods</title><p>A total of 5 patients with renal colic were recruited from April to May 2021. Ultrasound investigation was performed and pyelocalycoectasia was revealed. Patients signed a form of informed consent for a contrast CT with Omnipac 300.0 on a 64-slice CT scanner with 0.5 mm slice thickness Somatom Definition AS. The obtained images were studied in the program Medical Imaging Interaction Toolkit (MITK) that was used for 3D-reconstruction of PCS by the images of excretory phase and creation of a standard virtual model. Further, three random points were designated on each slice of the non-enhanced CT phase for the evaluation of the density differences around these points and determination of PCS boundaries without the need in their manual isolation (Fig. 1).</p><fig id="fig-1"><caption><p>Figure 1. Designation of points on the axial non-enhanced CT slices within the PCS: A — setting the first point; B — setting the second point; C — setting the third point and automated determination of the PCS boundaries</p></caption><graphic xlink:href="urovest-9-3-g001.jpeg"><uri content-type="original_file">https://cdn.elpub.ru/assets/journals/urovest/2021/3/zodyrvwcEpNamizWi2ykwuySxikOz1RC3cBP1PGn.jpeg</uri></graphic></fig><p>Further, automated mergence of the selected areas was performed. Due to a polygonality of the obtained 3D-constructions, the same algorithm was used for smoothing of the surface (Figs. 2-3).</p><fig id="fig-2"><caption><p>Figure 2. An example of virtual models, side view: A — automated PCS reconstruction using non-enhanced CT images before smoothing; B — non-enhanced 3D-reconstruction of the PCS after smoothing; C — 3D-reconstruction of the CT excretory phase</p></caption><graphic xlink:href="urovest-9-3-g002.jpeg"><uri content-type="original_file">https://cdn.elpub.ru/assets/journals/urovest/2021/3/NSRQk0LE0nEeDRneQoUDjQ9YEutL694XYEJ4Ija7.jpeg</uri></graphic></fig><fig id="fig-3"><caption><p>Figure 3. An example of virtual models, front view: A — automated PCS reconstruction using non-enhanced CT images before smoothing; B — non-enhanced 3D-reconstruction of the PCS after smoothing; C — 3D-reconstruction of the CT excretory phase</p></caption><graphic xlink:href="urovest-9-3-g003.jpeg"><uri content-type="original_file">https://cdn.elpub.ru/assets/journals/urovest/2021/3/kHLuRzadFgUTl6YlO2qW96TDgAMxTMUkb50BPu1q.jpeg</uri></graphic></fig><p>The volume of the obtained virtual models and the volume of contrast reconstructed models were compared. Five urologists evaluated the informative value of such reconstructions for the investigation of the PCS anatomy of a certain patient. The obtained models were also analyzed by IT specialists for suitability for 3D-printing.</p><p>Statistical analysis. The statistical analysis was made in the IBM SPSS Statistics 22.0 software (SPSS Inc., Chicago, IL, USA). The evaluation of nominal data was made with a chi-square test. The difference was significant at p &lt; 0.05.</p></sec><sec><title>Results</title><p>In all cases, the duration of PCS boundaries determination and its reconstruction with smoothing was less than 10 minutes. The mean surface area of contrast and non-enhanced 3D models was 3291 mm2 and 2879 mm2, respectively (p = 0.12). The comparison of contrast and non-enhanced 3D models as well as their evaluation and feasibility for preoperative planning scored 4.5 out of 5.0 by urologists. A discussion with engineers on the adequacy of the models for 3D-printing showed that all PCS parts were sufficiently visualized and did not require correction. Potentially weak parts of the printed-out models, in particular, minor calyx necks, did not require the formation of additional supports before printing. Thus, the models were completely suitable for potential 3D-printing.</p></sec><sec><title>Discussion</title><p>Non-enhanced CT provided a urologist with reliable information on the main parameters of ureteral stones that include size, site, and density. However, it is impossible to study in detail the renal cavity system, which requires additional diagnostic procedures for reliable planning of possible surgery. Up to now, 3D-reconstruction was possible only after contrast CT that has an excretory phase in 3-5 minutes. The high density of the contrast is comparable with the density of bone structures. And the filling of PCS provides a 3D reconstruction via an automated overlay of CT images. As a result, a urologist gets a possibility to evaluate all structural peculiarities of the renal cavity of a certain patient, in particular, the number and orientation of the minor calyces, length, and width of the necks, as well as the angle ratio between different parts of PCS. In turn, this information allows a specialist to choose proper tactics of the surgery for nephrolithiasis increasing the efficiency of the intervention and decreasing the rate of associated complications [<xref ref-type="bibr" rid="cit6">6</xref>].</p><p>The application of a contrast agent has such disadvantages as an increase in radiative exposure and load on a patient’s organism and a dependence on the patient’s state of health, in particular, impairments of renal excretory function. This makes the development of 3D methods of reconstruction by non-enhanced images a relevant task.</p><p>Automated reconstruction is possible for structures with a relatively constant shape without branching, like heart chambers [<xref ref-type="bibr" rid="cit7">7</xref>], aorta [<xref ref-type="bibr" rid="cit8">8</xref>], intracerebral hemorrhage [<xref ref-type="bibr" rid="cit9">9</xref>], and kidney parenchyma [<xref ref-type="bibr" rid="cit10">10</xref>]. This approach is not feasible for the renal cavity because of its variable and branchy structure, small differences in the density of the surrounding structures (vessels, adipose tissue), and collapsed shape of the renal cavity in the norm. The last aspect prevents the development of available solutions for previous limiting factors. The authors’ point of view is shared only in one publication (Sung et al.) on the description of 3D-reconstruction of PCS by the images of non-enhanced CT [<xref ref-type="bibr" rid="cit5">5</xref>]. Sung et al. proposed a protocol of intravenous infusion with diuretic load for artificial dilation of PCS before CT scanning. This approach showed to result in a significant volume of the renal cavity system reconstruction in comparison with the reconstruction of images made in the control group. The determination of PCS boundaries was performed manually by an IT specialist, which took more than 20 minutes and required sufficient experience. This limited the availability of this approach for routine application in medical institutions.</p><p>The present work included patients with renal colic that underwent CT scanning during the episode of obstruction that lead to a dilation sufficient for the visualization of the collecting system of a kidney. The determination of the boundaries was performed in a semi-automated mode. Several random points were designated within the boundaries of PCS in each non-enhanced CT image for the determination of its boundaries. After the mergence of the images, a 3D model was built. Further, the described algorithm automatically determined PCS boundaries significantly reducing the time of determination (to 5 minutes). This method did not require specialized experience and the procedure of segmenting could be performed by a urologist.</p><p>It should be mentioned that there were limitations in the present study. Firstly, the analysis included CT scans of five patients, which did not allow for the approbation of the described algorithm in the reconstruction of all variations of PCS. Secondly, the selected patients had nephrolithiasis complicated by the obstruction of the upper urinary tracts with dilation of PCS. Thus, this approach proved feasible in this cohort of patients. And thirdly, the reconstruction was performed in a semi-automated mode, which also required the involvement of the specialist in its realization. Finally, the described algorithm was not tested in patients with the presence of a stone in the PCS, which could negatively affect the precision of the automated determination of the boundaries. Further improvement of this algorithm will target a complete automated performance that will select the borders of PCS in all CT slices after the designation of one point.</p></sec><sec><title>Conclusion</title><p>A semi-automated reconstruction of the PCS by non-enhanced CT scans provides its possible visualization without enhancement in patients with an obstruction of the upper urinary tract.</p></sec></body><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Brisbane W, Bailey MR, Sorensen MD. An overview of kidney stone imaging techniques. Nat Rev Urol. 2016;13(11):654-62. DOI: 10.1038/nrurol.2016.154</mixed-citation><mixed-citation xml:lang="en">Brisbane W, Bailey MR, Sorensen MD. An overview of kidney stone imaging techniques. Nat Rev Urol. 2016;13(11):654-62. DOI: 10.1038/nrurol.2016.154</mixed-citation></citation-alternatives></ref><ref id="cit2"><label>2</label><citation-alternatives><mixed-citation xml:lang="ru">Rudnick MR, Leonberg-Yoo AK, Litt HI, Cohen RM, hilton S, Reese PP. The Controversy of contrast-Induced nephropathy with Intravenous contrast: What Is the risk? Am J Kidney Dis. 2020;75(1):105-13. DOI: 10.1053/j.ajkd.2019.05.022</mixed-citation><mixed-citation xml:lang="en">Rudnick MR, Leonberg-Yoo AK, Litt HI, Cohen RM, hilton S, Reese PP. The Controversy of contrast-Induced nephropathy with Intravenous contrast: What Is the risk? Am J Kidney Dis. 2020;75(1):105-13. DOI: 10.1053/j.ajkd.2019.05.022</mixed-citation></citation-alternatives></ref><ref id="cit3"><label>3</label><citation-alternatives><mixed-citation xml:lang="ru">Shimizu A, Ohno R, Ikegami T, Kobatake H, Nawano S, Smutek D. Segmentation of multiple organs in non-contrast 3D abdominal CT images. Int J CARS. 2007;2:135-42. DOI 10.1007/s11548-007-0135-z</mixed-citation><mixed-citation xml:lang="en">Shimizu A, Ohno R, Ikegami T, Kobatake H, Nawano S, Smutek D. Segmentation of multiple organs in non-contrast 3D abdominal CT images. Int J CARS. 2007;2:135-42. DOI 10.1007/s11548-007-0135-z</mixed-citation></citation-alternatives></ref><ref id="cit4"><label>4</label><citation-alternatives><mixed-citation xml:lang="ru">Parkhomenko E, O’Leary M, Safiullah S, Walia S, Owyong M, Lin C, James R, Okhunov Z, Patel RM, Kaler KS, Landman J, Clayman R. Pilot assessment of Immersive virtual reality Renal Models as an Educational and Preoperative Planning Tool for Percutaneous Nephrolithotomy. J Endourol. 2019;33(4):283-8. DOI: 10.1089/end.2018.0626</mixed-citation><mixed-citation xml:lang="en">Parkhomenko E, O’Leary M, Safiullah S, Walia S, Owyong M, Lin C, James R, Okhunov Z, Patel RM, Kaler KS, Landman J, Clayman R. Pilot assessment of Immersive virtual reality Renal Models as an Educational and Preoperative Planning Tool for Percutaneous Nephrolithotomy. J Endourol. 2019;33(4):283-8. DOI: 10.1089/end.2018.0626</mixed-citation></citation-alternatives></ref><ref id="cit5"><label>5</label><citation-alternatives><mixed-citation xml:lang="ru">Sung JM, Jefferson FA, Tapiero S, Patel RM, Owyong M, Xie L, Karani R, Ghamarian P, Lall C, Clayman RV, Landman J. evaluation of a diuresis enhanced non-contrast computed tomography for kidney stones protocol to maximize Collecting System Distention. J Endourol. 2020;34(3):255-61. DOI: 10.1089/end.2019.0719</mixed-citation><mixed-citation xml:lang="en">Sung JM, Jefferson FA, Tapiero S, Patel RM, Owyong M, Xie L, Karani R, Ghamarian P, Lall C, Clayman RV, Landman J. evaluation of a diuresis enhanced non-contrast computed tomography for kidney stones protocol to maximize Collecting System Distention. J Endourol. 2020;34(3):255-61. DOI: 10.1089/end.2019.0719</mixed-citation></citation-alternatives></ref><ref id="cit6"><label>6</label><citation-alternatives><mixed-citation xml:lang="ru">Türk C, Petřík A, Sarica K, Seitz C, Skolarikos A, Straub M, Knoll T. EAU guidelines on Interventional treatment for urolithiasis. Eur Urol. 2016;69(3):475-82. DOI: 10.1016/j.eururo.2015.07.041</mixed-citation><mixed-citation xml:lang="en">Türk C, Petřík A, Sarica K, Seitz C, Skolarikos A, Straub M, Knoll T. EAU guidelines on Interventional treatment for urolithiasis. Eur Urol. 2016;69(3):475-82. DOI: 10.1016/j.eururo.2015.07.041</mixed-citation></citation-alternatives></ref><ref id="cit7"><label>7</label><citation-alternatives><mixed-citation xml:lang="ru">Shahzad R, Bos D, Budde RP, Pellikaan K, Niessen WJ, van der Lugt A, van Walsum T. Automatic segmentation and quantification of the cardiac structures from non-contrast-enhanced cardiac CT scans. Phys Med Biol. 2017;62(9):3798-813. DOI: 10.1088/1361-6560/aa63cb</mixed-citation><mixed-citation xml:lang="en">Shahzad R, Bos D, Budde RP, Pellikaan K, Niessen WJ, van der Lugt A, van Walsum T. Automatic segmentation and quantification of the cardiac structures from non-contrast-enhanced cardiac CT scans. Phys Med Biol. 2017;62(9):3798-813. DOI: 10.1088/1361-6560/aa63cb</mixed-citation></citation-alternatives></ref><ref id="cit8"><label>8</label><citation-alternatives><mixed-citation xml:lang="ru">Sedghi Gamechi Z, Bons LR, Giordano M, Bos D, Budde RPJ, Kofoed KF, Pedersen JH, Roos-Hesselink JW, de Bruijne M. Automated 3D segmentation and diameter measurement of the thoracic aorta on non-contrast enhanced CT. Eur Radiol. 2019;29(9):4613-23. DOI: 10.1007/s00330-018-5931-z</mixed-citation><mixed-citation xml:lang="en">Sedghi Gamechi Z, Bons LR, Giordano M, Bos D, Budde RPJ, Kofoed KF, Pedersen JH, Roos-Hesselink JW, de Bruijne M. Automated 3D segmentation and diameter measurement of the thoracic aorta on non-contrast enhanced CT. Eur Radiol. 2019;29(9):4613-23. DOI: 10.1007/s00330-018-5931-z</mixed-citation></citation-alternatives></ref><ref id="cit9"><label>9</label><citation-alternatives><mixed-citation xml:lang="ru">Patel A, Schreuder FHBM, Klijn CJM, Prokop M, Ginneken BV, Marquering HA, Roos YBWEM, Baharoglu MI, Meijer FJA, Manniesing R. Intracerebral Haemorrhage Segmentation in Non-Contrast CT. Sci Rep. 2019;9(1):17858. DOI: 10.1038/s41598-019-54491-6</mixed-citation><mixed-citation xml:lang="en">Patel A, Schreuder FHBM, Klijn CJM, Prokop M, Ginneken BV, Marquering HA, Roos YBWEM, Baharoglu MI, Meijer FJA, Manniesing R. Intracerebral Haemorrhage Segmentation in Non-Contrast CT. Sci Rep. 2019;9(1):17858. DOI: 10.1038/s41598-019-54491-6</mixed-citation></citation-alternatives></ref><ref id="cit10"><label>10</label><citation-alternatives><mixed-citation xml:lang="ru">Khalifa F, Elnakib A, Beache GM, Gimel’farb G, El-Ghar MA, Ouseph R, Sokhadze G, Manning S, McClure P, El-Baz A. 3D kidney segmentation from CT images using a level set approach guided by a novel stochastic speed function. Med Image Comput Assist Interv. 2011;14(3):587-94. DOI: 10.1007/978-3-642-23626-6_72</mixed-citation><mixed-citation xml:lang="en">Khalifa F, Elnakib A, Beache GM, Gimel’farb G, El-Ghar MA, Ouseph R, Sokhadze G, Manning S, McClure P, El-Baz A. 3D kidney segmentation from CT images using a level set approach guided by a novel stochastic speed function. Med Image Comput Assist Interv. 2011;14(3):587-94. DOI: 10.1007/978-3-642-23626-6_72</mixed-citation></citation-alternatives></ref></ref-list><fn-group><fn fn-type="conflict"><p>The authors declare that there are no conflicts of interest present.</p></fn></fn-group></back></article>
