دورية أكاديمية
CNN application for automated determination of the patient's size to obtain the size-specific dose estimated in CT.
| العنوان: | CNN application for automated determination of the patient's size to obtain the size-specific dose estimated in CT. |
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| المؤلفون: | Hernández-Dávila ER; Facultad de Ciencias de Ciencias de la Conducta, Universidad Autónoma del Estado de México, Toluca, México, Mexico., Torres-García E; Facultad de Medicina, Universidad Autónoma del Estado de México, Toluca, México, Mexico., Aranda-Lara L; Facultad de Medicina, Universidad Autónoma del Estado de México, Toluca, México, Mexico., Roldan-Valadez E; Division of Research, Instituto Nacional de Rehabilitación 'Luis Guillermo Ibarra Ibarra', 14389, Mexico City, Mexico., Isaac-Olivé K; Facultad de Medicina, Universidad Autónoma del Estado de México, Toluca, México, Mexico., Flores-Reyes M; Facultad de Medicina, Universidad Autónoma del Estado de México, Toluca, México, Mexico.; Universidad Estatal del Valle de Toluca, Ocoyoacac, México, Mexico. |
| المصدر: | Biomedical physics & engineering express [Biomed Phys Eng Express] 2024 Apr 26; Vol. 10 (3). Date of Electronic Publication: 2024 Apr 26. |
| نوع المنشور: | Journal Article; Research Support, Non-U.S. Gov't |
| اللغة: | English |
| بيانات الدورية: | Publisher: IOP Publishing Ltd Country of Publication: England NLM ID: 101675002 Publication Model: Electronic Cited Medium: Internet ISSN: 2057-1976 (Electronic) Linking ISSN: 20571976 NLM ISO Abbreviation: Biomed Phys Eng Express Subsets: MEDLINE |
| أسماء مطبوعة: | Original Publication: Bristol : IOP Publishing Ltd., [2015]- |
| مواضيع طبية MeSH: | Tomography, X-Ray Computed*/methods , Radiation Dosage* , Algorithms*, Humans ; Male ; Female ; Body Size ; Neural Networks, Computer ; Software ; Automation ; Thorax/diagnostic imaging ; Adult ; Abdomen/diagnostic imaging ; Radiometry/methods ; Radiography, Thoracic/methods ; Middle Aged ; Image Processing, Computer-Assisted/methods ; Radiography, Abdominal/methods ; Aged |
| مستخلص: | Introduction . The currently available dosimetry techniques in computed tomography can be inaccurate which overestimate the absorbed dose. Therefore, we aimed to provide an automated and fast methodology to more accurately calculate the SSDE usingDwobtained by using CNN from thorax and abdominal CT study images. Methods . The SSDE was determined from the 200 records files. For that purpose, patients' size was measured in two ways: (a) by developing an algorithm following the AAPM Report No. 204 methodology; and (b) using a CNN according to AAPM Report No. 220. Results . The patient's size measured by the in-house software in the region of thorax and abdomen was 27.63 ± 3.23 cm and 28.66 ± 3.37 cm, while CNN was 18.90 ± 2.6 cm and 21.77 ± 2.45 cm. The SSDE in thorax according to 204 and 220 reports were 17.26 ± 2.81 mGy and 23.70 ± 2.96 mGy for women and 17.08 ± 2.09 mGy and 23.47 ± 2.34 mGy for men. In abdomen was 18.54 ± 2.25 mGy and 23.40 ± 1.88 mGy in women and 18.37 ± 2.31 mGy and 23.84 ± 2.36 mGy in men. Conclusions . Implementing CNN-based automated methodologies can contribute to fast and accurate dose calculations, thereby improving patient-specific radiation safety in clinical practice. (© 2024 IOP Publishing Ltd.) |
| فهرسة مساهمة: | Keywords: convolutional neural network; medical image segmentation; size specific dose estimate; tomography dosimetry |
| تواريخ الأحداث: | Date Created: 20240417 Date Completed: 20240426 Latest Revision: 20240426 |
| رمز التحديث: | 20240426 |
| DOI: | 10.1088/2057-1976/ad3fbe |
| PMID: | 38631317 |
| قاعدة البيانات: | MEDLINE |
Full Text Finder | تدمد: | 2057-1976 |
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| DOI: | 10.1088/2057-1976/ad3fbe |