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An Automatic Approach for Bone Tumor Detection from Non-Standard CT Images
Un enfoque automático para la detección de tumores óseos a partir de imágenes de CT no estándar
DOI:
https://doi.org/10.15446/ing.investig.90748Keywords:
CT, medical image processing, region growing algorithm, bone tumor, 3D (en)CT, procesamiento de imágenes médica, algoritmo de crecimiento regional, tumor óseo, 3D (es)
Image processing techniques are applied in many fields of science. This study aims to detect tumors in the foot and create 3D models via computed tomography (CT), as well as to produce biometric data. 1 039 CT images were obtained from a server. The parameters used were a collimation of 64 detectors, a scanning thickness of 0,5-3 mm, and a pixel size of 512 x 512, with a radiometric resolution of the 16-bit gray levels. Noise reduction, segmentation, and morphological analysis were performed on CT scans to detect bone tumors. In addition, this study used digital image processing techniques to create a virtual three-dimensional (3D) model of bone tumors. The performance of our proposal was evaluated by analyzing the receptor operating characteristics (ROC). According to the results, the sensitivity, specificity, and precision in tumor detection were 0,96, 1, and 0,98%, respectively, with a 0,99% average F-measure. Radiologist reports were used for the sake of comparison. The proposed technique for detecting bone tumors of the foot via CT can help radiologists with its increased precision, sensitivity, specificity, and F-measure. This method could improve the diagnosis of foot and ankle tumors by allowing for the multidirectional quantification of abnormalities.
Las técnicas de procesamiento de imágenes se aplican en muchos campos de la ciencia. El objetivo de este estudio es detectar tumores en el pie y crear modelos 3D mediante tomografía computarizada (CT), así como producir datos biométricos. 1 039 imágenes de CT se obtuvieron de un servidor. Los parámetros utilizados fueron una colimación 64 detectores, un grosor de escaneo de 0,5-3 mm y un tamaño del píxel de 512 x 512, con una resolución radiométrica de niveles de gris de 16 bits. Se realizó reducción de ruido, segmentación y análisis morfológico a imágenes CT para detectar tumores óseos. Adicionalmente, en este estudio se aplicaron técnicas de procesamiento de imágenes digitales para crear un modelo virtual tridimensional (3D) de tumor óseo. El rendimiento de nuestra propuesta se evaluó con base en el análisis de las características operativas del receptor (ROC). Según los resultados, la sensibilidad, la especificidad y la precisión en la detección de tumores fue de 0,96, 1, 0,98 % respectivamente, con un F-measure promedio de 0,99 %. Se utilizaron reportes de radiología para efectos de comparación. La técnica propuesta para detectar tumores óseos del pie mediane CT puede ayudar a los radiólogos dada su alta precisión, sensibilidad, especificidad y F-measure. Este método puede mejorar el diagnóstico de tumores de pie y tobillo al permitir la cuantificación multidireccional de anomalías.
References
Aydın, M., and Kurnaz, T. F. (2023). An alternative method for the particle size distribution: Image processing. Turkish Journal of Engineering, 7(2), 108-115. https://doi.org/10.31127/tuje.1053462
Akcay, O., Erenoglu, R. C., and Avsar, E. O. (2017). The effect of jpeg compression inclose-range photogrammetry. International Journal of Engineering and Geosciences, 2(1), 35-40. https://doi.org/10.26833/ijeg.287308
Bakotic, B., and Huvos, A. G. (2001). Tumors of the bones of the feet: The clinicopathologic features of 150 cases. Journal of Foot & Ankle Surgery, 40(5), 277-286. https://doi.org/10.1016/S1067-2516(01)80063-6
Basile, A. (2012). Subjective results after surgical treatment for displaced intraarticular calcaneal fractures. Journal of Foot and Ankle Surgery, 51, 182-186. https://doi.org/10.1053/j.jfas.2011.10.042
Bestic, J. M., Wessell, D. E., Beaman, F. D., Cassidy, R. C., Czucz-man, G. J., Demertzis, J. L., Lenchik, L., Motamedi, K., Pierce, J. L., Sharma, A., Sloan, A. E., Than, K., Walker, E. A., Yung, E. Y. K., and Kransdorf, M. J. (2020). ACR appropriateness criteria: Primary bone tumors. Journal of the American College of Radiology, 17(5S),S226-S238. https://doi.org/10.1016/j.jacr.2020.01.038
Campbell, C. J., and Leupold, R. G. (1973). Tumours and tumour-like conditions of the os calcis. Orthopedic Clinics of North America, 4,145-156. https://doi.org/10.1016/S0030-5898(20)30510-1
Catal Reis, H. (2010). Metric analysis of orthopedic changes of ballerina’s foot bones by photogrammetric techniques [Mas-ter’s thesis, Selcuk University]. http://acikerisimarsiv.selcuk.edu.tr:8080/xmlui/handle/123456789/660.
Catal Reis, H. (2018). Detection of foot bone anomaly using medical photogrammetry. International Journal of Engineering and Geosciences, 3(1), 001-005. https://doi.org/10.26833/ijeg.333686
Costelloe, C. M., and Madewell, J. E. (2013). Radiography in the initial diagnosis of primary bone tumors. American Journal of Roentgenology, 200, 3-7. https://doi.org/10.2214/AJR.12.8488
Diémé, C., Dembélé, B., Gaye, A.M., Sarr, L., Coundoul, C., Gueye, A.B., Déme, H., Sané, A., and Seye, S. (2015). Osteosarcoma of the calcaneus: A case report. Médecine et Chirurgie du Pied, 31, 69-71. https://doi.org/10.1007/s10243-015-0407-1
Doğan, Y., and Yakar, M. (2018). GIS and three-dimensional modeling for cultural heritages. International Journal of Engi-neering and Geosciences, 3(2), 50-55. https://doi.org/10.26833/ijeg.378257
Eckstein, F., Cicuttini, F., Raynauld, J.P., Waterton, J.C., and Peterfy, C. (2006). Magnetic resonance imaging (MRI) of articular cartilage in knee osteoarthritis (OA): Morphological assessment. Osteoarthritis and Cartilage, 14(1), 46-75. https://doi.org/10.1016/j.joca.2006.02.026
Epstein. N., Chandran. S., and Chou. L. (2012). Current concepts review: Intra-articular fractures of the calcaneus. Foot & Ankle International, 33, 79-86. https://doi.org/10.3113/FAI.2012.0079
Esim A. K., Kaya, H., and Alcan, V. (2019). Determination of malignant melanoma by analysis of variation values. Turkish Journal of Engineering, 3(3), 120-126. https://doi.org/10.31127/tuje.472328
Foo, L. F., and Raby, N. (2005). Tumors and tumor-like lesions in the foot and ankle. Clinical Radiology, 60, 308-332. https://doi.org/10.1016/j.crad.2004.05.010
Gemescu, I. N., Thierfelder, K. M., Rehnitz, C., and Weber, M.-A. (2019). Imaging features of bone tumors conventional radio-graphs and MR imaging correlation. Magnetic Resonance Imaging Clinics of North America, 27, 753–767. https://doi.org/10.1016/j.mric.2019.07.008
Ghafouri-Fard, S., Shoorei, H., and Taheri, M. (2020). Role of microRNAs in the development, prognosis and therapeutic response of patients with prostate cancer. Gene, 759, 144995. https://doi.org/10.1016/j.gene.2020.144995
González, R. C., and Woods, R. E. (2007). Digital image processing (2nd ed.). Publishing House of Electronics Industry.
Goodyear, M. D., Krleza-Jeric, K., and Lemmens, T. (2007). The declaration of Helsinki. British Medical Journal, 335, 624-625. https://doi.org/10.1136/bmj.39339.610000.BE
Gutekunst, D. J., Liu, L., Ju, T., Prior, F. W., and Sinacore, D. R. (2013). Reliability of clinically relevant 3D foot bone angles from quantitative computed tomography. Journal of Foot and Ankle Research, 6, 38. https://doi.org/10.1186/1757-1146-6-38
Hapani, H., Kalola, J., and Hapani, J. (2014). Comparative role of CT scan and MR imaging in primary malignant bone tumors. IOSR Journal of Dental and Medical Sciences, 13(11), 29-35. https://doi.org/10.9790/0853-131172935
Hasbek, Z., Salk, I., Yucel, B., Yucel, B., and Babacan, N. A. (2013). Which imaging method to choose for detection of bone metastases? Bone scintigraphy, CT, 18F-FDG PET/CT or MR? Bozok Medical Journal, 3(3),44-50. https://dergipark.org.tr/tr/download/article-file/43180
Hosseini, A., Mirzaei, A., Salimi, V., Jamshidi, K., Babaheidarian, P., Fallah, S., Rampisheh, Z., Khademian, N., Abdolbahavi, Z., Bahrabadi, M., Ibrahimi, M., Hosami, F., and Tavakoli-Yaraki, M. (2020). The local and circulating SOX9 as a potential biomarker for the diagnosis of primary bone cancer. Journal of Bone Oncology, 23, 100300. https://doi.org/10.1016/j.jbo.2020.100300
Kamal, F., Waryudia, A., Effendia, Z., and Kodrat, E. (2016). Management of aggressive giant cell tumor of calcaneal bone: A case report. International Journal of Surgery Case Reports, 28, 176-181. https://doi.org/10.1016/j.ijscr.2016.09.038
Kilgore, W. B., and Parrish, W. M. (2005). Calcaneal tumors and tumor-like conditions. Foot and Ankle Clinics, 10(3), 541-565. https://doi.org/10.1016/j.fcl.2005.05.002
Ladd, M. L., Roth, T. D. (2017). Computed tomography and magnetic resonance imaging of bone tumors. Seminars in Roentgenology, 52(4), 209-226. https://doi.org/10.1053/j.ro.2017.04.006
Lodwick, G. S., Haun, C. L., Smith, W. E., Keller, R. F., and Robert-son, E. D. (1963). Computer diagnosis of primary bone tumors. Radiology, 80, 273-275. https://doi.org/10.1148/80.2.273
Mehta, K., McBee, M. P., Mihal, D. C., and England, E. B. (2017). Radiographic analysis of bone tumors: a systematic approach. Seminars in Roentgenology, 52(4), 194-208. https://doi.org/10.1053/j.ro.2017.04.002
Mistry, K. D., and Talati, B. J. (2016, Oct. 6-8). Integrated approach for bone tumor detection from MRI scan imagery [Conference presentation]. 2016 International Conference on Signal and Information Processing (IConSIP), Vishnupuri, India. https://doi.org/10.1109/ICONSIP.2016.7857471
Nishikawa, R. M. (2005). Computer-assisted detection and diagnosis. Wiley. DOI: https://doi.org/10.1002/0471732877.emd310
Nurtanio, I., Astuti, E. R., Purnama, I. K. E., Hariadi, M., Purnomo, M. H. (2013). Classifying cyst and tumor lesion using support vector machine based on dental panoramic images texture features. IAENG International Journal of Computer Science, 40, 1-4. https://www.iaeng.org/IJCS/issues_v40/issue_1/IJCS_40_1_04.pdf
Ozer, D., Aycan, O. E., Er, S. T., Tanritanir, R., Arikan, Y., and Ka-bukcuoglu, Y. S. (2017). Primary tumor and tumor-like lesions of bones of the foot: Single-center experience of 166 cases. Journal of Foot & Ankle Surgery, 56, 1180-1187. https://doi.org/10.1053/j.jfas.2017.05.027
Parker, E. R. (2021). The influence of climate change on skin cancer incidence – A review of the evidence. International Journal of Women’s Dermatology, 7(1), 17-27. https://doi.org/10.1016/j.ijwd.2020.07.003
Pirak, J., Brandeisky, J. A., Simon, P., and Khaladj, M. (2020). Elastofibroma in the rear foot: A case report of a rare soft tissue tumor. Journal of Foot & Ankle Surgery, 59, 587-589. https://doi.org/10.1053/j.jfas.2019.09.021
Plodkowski, A. J., Arimatei, J., Araujo-Filho, B., Simmers, C. D. A., Girshman, J., Raj, M., Zheng, J., Rimner, A., and Ginsberg, M. S. (2021). Pre-treatment CT imaging in stage IIIA lung cancer: Can we predict local recurrence after definitive chemoradiotherapy? Clinical Imaging, 69, 133-138. https://doi.org/10.1016/j.clinimag.2020.07.005
Qiang, M., Chen, Y., Zhang, K., Li, H., and Dai, H. (2014). Meas-urement of three-dimensional morphological characteristics of the calcaneus using CT image post-processing. Journal of Foot and Ankle Research, 7, 19. https://doi.org/10.1186/1757-1146-7-19
Reddy, K. K., Anisha, P. R., and Prasad, L. N. (2015). A novel approach for detecting the bone cancer and its stage based on mean intensity and tumor size. Medicine, Recent Researches in Applied Computer Science, 162-171. https://www.semanticscholar.org/paper/A-Novel-Approach-for-Detecting-the-Bone-Cancer-and-Reddy-Prasad/6214771aac055643a74a94a52287cb69dacbd2a8
Riis, M. (2020). Modern surgical treatment of breast cancer. Annals of Medicine and Surgery, 56, 95-107. https://doi.org/10.1016/j.amsu.2020.06.016
Scotto di Carlo, F., Whyte, M. P., and Gianfrancesco, F. (2020). The two faces of giant cell tumor of bone. Cancer Letters, 489,1-8. https://doi.org/10.1016/j.canlet.2020.05.031
Tasdemir, Ş., and Ozkan, I. A. (2019). ANN approach for estima-tion of cow weight depending on photogrammetric body dimensions. International Journal of Engineering and Geosciences, 4(1), 036-044. https://doi.org/10.26833/ijeg.427531
Toepfer, A. (2017). Tumors of the foot and ankle – A review of the principles of diagnostics and treatment. Fuß & Sprunggelenk, 15, 82-96. https://doi.org/10.1016/j.fuspru.2017.03.004
Yan, L., Zong, J., Chu, J., Wang, W., Li, M., Wang, X., Song, M., and Wang, S. (2018). Primary tumours of the calcaneus (Review). Oncology Letters, 15, 8901-8914, https://doi.org/10.3892/ol.2018.8487
Young, P. S., Bell, S. W., MacDuff, E. M., and Mahendra, A. (2013). Primary osseous tumors of the hind-foot: Why the delay in diagnosis and should we be concerned. Clinical Orthopaedics and Related Research, 471, 871‑877. https://doi.org/10.1007/s11999-012-2570-6
Weilbaecher, K. N., Guise, T. A., and McCauley, L. K. (2011). Cancer to bone: A fatal attraction. Nature Reviews: Cancer, 11, 411-425. https://doi.org/10.1038/nrc3055
Zilberman, Y., and Sonkusale S. R. (2015). Microfluidic optoelec-tronic sensor for salivary diagnostics of stomach cancer. Biosensors and Bioelectronics, 6715, 465-471. https://doi.org/10.1016/j.bios.2014.09.006
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