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An Image-guided Endoscope System for the Ureter Detection

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Abstract

The ureter injury occasionally happens in the gynecology, abdominal and urinary surgeries. The medical negligence may cause severe problems for the hospital, and mental pressure for the doctors. Furthermore, the serious accident brings painful complications for the patients. Thus, it is necessary to locate the ureter, which is covered by peritoneum and connective tissue, for the assisted surgery. The aim is to detect the ureter position, and avoid iatrogenic ureter injury. In order to indicate the ureter position in surgery, we propose an image-guided endoscope system that has both traditional functions of the endoscope system and the additional function of ureter detection. We design an infrared-based pipe that its shape is similar to the ureteral catheter to mark the ureter, and use the multi-spectral camera that can capture both the visual and infrared light to obtain the endoscopic images. To extract the precise contour of the ureter, we propose a hardware-aided detection method, and a high-efficient segmentation algorithm. The hardware-aided method is used to recognize the kind of the captured images. Then the ureter position is extract by the segmentation algorithm. Before the image segmentation, the image enhancement and denoising algorithms are executed to reduce the noise level of images. The extracted contour of the ureter is fused with visible-light images to generate the endoscopic images highlighting the location of ureter. Experimental results indicate that the proposed system can achieve 83.54% and 88.38% of true positive rate (TPR) and positive predictive value (PPV ) respectively. In addition, the frame rate is about 25 frames per second (f/s), which reaches the real-time performance. We proposed a novel image-guided endoscope system for the ureter detection, and the ureter position can be displayed during the surgery. The proposed system may reduce the ureter injury in surgery, and improve the surgical success rate.

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References

  1. Tsui C, Klein R, Garabrant M (2013) Minimally invasive surgery: national trends in adoption and future directions for hospital strategy. Surg Endosc 27(7):2253–2257

    Article  Google Scholar 

  2. Koeda K, Nishizuka S, Go W (2011) Minimally invasive surgery for gastric cancer: the future standard of care. World J Surg 35(7):1469–1477

    Article  Google Scholar 

  3. Son T, Hyung WJ, Lee JH, Kim YM, Noh SH (2014) Minimally invasive surgery for serosa-positive gastric cancer (pt4a) in patients with preoperative diagnosis of cancer without serosal invasion. Surg Endosc 28 (3):866–874

    Article  Google Scholar 

  4. Ranzani T, Cianchetti M, Gerboni G, De Falco I, Menciassi A (2016) A soft modular manipulator for minimally invasive surgery Design and characterization of a single module. IEEE Trans Robot 32(1):187–200

    Article  Google Scholar 

  5. Oh . S-Y, Kwon S, Lee K-G, Suh Y-S, Choe H-N, Kong S-H, Lee H-J, Kim Woo Ho, Yang H-K (2014) Outcomes of minimally invasive surgery for early gastric cancer are comparable with those for open surgery: analysis of 1,013 minimally invasive surgeries at a single institution. Surg Endosc 28(3):789–795

    Article  Google Scholar 

  6. Burdall OC, Boddy AP, Fullick J, Blazeby J, Krysztopik R, Streets C, Hollowood A, Barham CP, Titcomb D (2015) A comparative study of survival after minimally invasive and open oesophagectomy. Surg Endosc 29(2):431–437

    Article  Google Scholar 

  7. In Gyu Kwon, In Cho, Guner Ali, Choi Yoon Young, Shin Hyun Beak, Kim Hyoung-Il, Ji Yeong An, Cheong Jae-Ho, Noh Sung Hoon, Hyung Woo Jin (2014) Minimally invasive surgery for remnant gastric cancer: a comparison with open surgery. Surg Endosc 28(8):2452–2458

    Article  Google Scholar 

  8. Uttley L, Campbell F, Rhodes M, Cantrell A, Stegenga H, Lloyd-Jones M (2013) Minimally invasive oesophagectomy versus open surgery: is there an advantage? Surg Endosc 27(3):724–731

    Article  Google Scholar 

  9. Rossitto C, Gueli Alletti S, Costantini B, Fanfani F, Scambia G (2016) Total laparoscopic hysterectomy with percutaneous (percuvance (tm)) instruments: new frontier of minimally invasive gynecological surgery. J Minim Invasive Gynecol 23(1):14–15

    Article  Google Scholar 

  10. Celle C, Pomés C, Durruty G, Zamboni M, Cuello M (2015) Total laparoscopic hysterectomy with previous cesarean section using a standardized technique: experience of pontificia universidad catolica de chile. Gynecol Surg 12(3):149–155

    Article  Google Scholar 

  11. Xue M, Chen X, Shi L, Si J, Wang L, Chen S (2015) Small-bowel capsule endoscopy in patients with unexplained chronic abdominal pain: a systematic review. Gastrointest Endosc 81(1):186

    Article  Google Scholar 

  12. Egnatios J, Kaushal K, Kalmaz D, Zarrinpar A (2015) Video capsule endoscopy in patients with chronic abdominal pain with or without associated symptoms A retrospective study. Plos One 10(4):e0126509

    Article  Google Scholar 

  13. Liang X (2017) Clinical application of capsule endoscopy in the diagnosis of chronic abdominal pain. J Math Med 30(10):1469–1470

    Google Scholar 

  14. Chew BH, Lange D (2016) The future of ureteroscopy. Minerva Urologica E Nefrologica 68(6):592–597

    Google Scholar 

  15. Nakayama T, Numao N, Yoshida S, Ishioka J, Matsuoka Y, Saito K, Fujii Y, Kihara K (2016) A novel interactive educational system in the operating room–the ie system. Bmc Medical Education 16(1):44

    Article  Google Scholar 

  16. Andersen P, Andersen LM, Iversen LH (2015) Iatrogenic ureteral injury in colorectal cancer surgery: a nationwide study comparing laparoscopic and open approaches. Surg Endosc 29(6):1406–12

    Article  Google Scholar 

  17. Packiam VT, Cohen AJ, Pariser JJ, Bales GT (2016) The impact of minimally invasive surgery on major iatrogenic ureteral injury and subsequent ureteral repair during hysterectomy: a national analysis of risk factors and outcomes. Urol 98:183

    Article  Google Scholar 

  18. Karakan T, Kilinc MF, Demirbas A, Hascicek AM, Doluoglu OG, Yucel MO, Resorlu B (2016) Evaluating ureteral wall injuries with endoscopic grading system and analysis of the predisposing factors. J Endourol 30(4):S230

    Article  Google Scholar 

  19. Orr WS, Pisters LL, Rodriguez-Bigas MA (2015) Intraoperative ureteral injury. Gastrointestinal Surgery: Management of Complex Perioperative Complications 34:361–370

    Google Scholar 

  20. Acher C, Agarwal S (2017) Injury of the kidney, ureter, and bladder. In: Degiannis E (ed) Penetrating trauma. Springer, New York, pp 387–396

    Google Scholar 

  21. Song Q, Jianghai JI, Zhang X, Tian L, Ren Na, Sun J, Department Of Gynaecology (2016) The health economics research of ureteroscopy in the treatment of ureteral injury with gynecological laparoscopic surgery. China Continuing Medical Education 8(01):82–83

    Google Scholar 

  22. Zhang N, Zhai Z, Ge L, Guo L, Ma Y, Shan Z, Han Q, Department Of Urology (2017) Randomized controlled study of ureteral catheter on the prevention of ureteral injury during the gynecologic laparoscopic surgery running title:prevention of ureteral injury. J Modern Oncol 25(07):1116–1118

    Google Scholar 

  23. Chung D, Briggs J, Turney BW, Tapping CR (2016) Management of iatrogenic ureteric injury with retrograde ureteric stenting: an analysis of factors affecting technical success and long-term outcome. Acta Radiol 58(2):170–175

    Article  Google Scholar 

  24. Lucas JJ, Bermejo CE (2015) Preoperative ureteral catheter placement to prevent ureteral injuries, vol 31. Springer, New York, pp 245–246

    Google Scholar 

  25. Fu W-J, Wang Z-X, Li G, Cui F-Z, Zhang Y, Zhang X (2012) Comparison of a biodegradable ureteral stent versus the traditional double-j stent for the treatment of ureteral injury: an experimental study. Biomed Mater 7(6):065002

    Article  Google Scholar 

  26. Senagore AJ, Luchtefeld M (1994) An initial experience with lighted ureteral catheters during laparoscopic colectomy. J Laparoendosc Surg 4(6):399–403

    Article  Google Scholar 

  27. Teichman JM, Lackner JE, Harrison JM (1997) Comparison of lighted ureteral catheter luminance for laparoscopy. Tech Urol 3(4):213–215

    Google Scholar 

  28. Korb ML, Huh WK, Boone JD, Warram JM, Chung TK, De Boer E, Bland KI, Rosenthal EL (2015) Laparoscopic fluorescent visualization of the ureter with intravenous irdye800cw. J Minim Invasive Gynecol 22(5):799–806

    Article  Google Scholar 

  29. Siddighi S, Yune JJ, Hardesty J (2014) Indocyanine green for intraoperative localization of ureter. Am J Obstet Gynecol 211(4):1–2

    Article  Google Scholar 

  30. Tanaka E, Ohnishi S, Laurence RG, Choi HS, Humblet V, Frangioni JV (2007) Real-time intraoperative ureteral guidance using invisible near-infrared fluorescence. J Urol 178(5):2197–2202

    Article  Google Scholar 

  31. Verbeek FP, Van Der Vorst Jr, Schaafsma BE, Swijnenburg RJ, Gaarenstroom KN, Elzevier HW, Van De Velde C, Frangioni JV, Vahrmeijer AL (2013) Intraoperative near infrared fluorescence guided identification of the ureters using low dose methylene blue: A first in human experience. J Urol 190(2):574–579

    Article  Google Scholar 

  32. Al-Taher M, van den Bos J, Schols RM, Bouvy ND, Stassen LPS (2016) Fluorescence ureteral visualization in human laparoscopic colorectal surgery using methylene blue. J Laparoendosc Adv Surg Tech A 26 (11):870–875

    Article  Google Scholar 

  33. Song E, Yu F, Liu H, Cheng N, Li Y, Jin L, Hung C-C (2016) A novel endoscope system for position detection and depth estimation of the ureter. J Med Syst 40(12):266

    Article  Google Scholar 

  34. Doba N, Fukuda H, Numata K, Hao Y., Hara K, Nozaki A, Kondo M, Chuma M, Tanaka K, Takebayashi S (2017) A new device for fiducial registration of image-guided navigation system for liver rfa. Int J Comput Assist Radiol Surg 13(1):115–124

    Article  Google Scholar 

  35. Black D, Hansen C, Nabavi A, Kikinis R, Hahn H (2017) A survey of auditory display in image-guided interventions. Int J Comput Assist Radiol Surg 13(10):1665–1676

    Article  Google Scholar 

  36. Li M, Hansen C, Rose G (2017) A software solution to dynamically reduce metallic distortions of electromagnetic tracking systems for image-guided surgery. Int J Comput Assist Radiol Surg 12(9):1621–1633

    Article  Google Scholar 

  37. Fraeman AA, Murchie SL, Arvidson RE, Clark RN, Morris RV, Rivkin AS, Vilas F (2014) Spectral absorptions on phobos and deimos in the visible/near infrared wavelengths and their compositional constraints. Icarus 229(2):196–205

    Article  Google Scholar 

  38. Yuan LT, Swee SK, Ping T (2015) Infrared image enhancement using adaptive trilateral contrast enhancement. Pattern Recogn Lett 54:103–108

    Article  Google Scholar 

  39. Goodall TR, Bovik AC, Paulter NG (2016) Tasking on natural statistics of infrared images. IEEE Trans Image Process 25(1):65–79

    Article  MathSciNet  Google Scholar 

  40. Fan X, Shi P, Ni J, Li M (2015) A thermal infrared and visible images fusion based approach for multitarget detection under complex environment. Math Probl Eng 2015(9):1774–1783

    Google Scholar 

  41. Zhou Y, Huo S, Xiang W, Hou C, Kung SY (2018) Semi-supervised salient object detection using a linear feedback control system model. IEEE Transactions on Cybernetics, https://doi.org/10.1109/TCYB.2018.2793278

  42. Huo S, Zhou Y, Lei J, Ling N, Hou C (2017) Linear feedback control system based salient object detection. IEEE Transactions on Multimedia, https://doi.org/10.1109/TMM.2017.2769801

    Article  Google Scholar 

  43. Zheng Y, Wu D, Ke Y, Yang C, Chen M, Zhang G (2017) Online cloud transcoding and distribution for crowdsourced live game video streaming. IEEE Trans Circuits Syst Video Technol 27(8):1777–1789

    Article  Google Scholar 

  44. Liu L, Yang N, Lan J, Li J (2015) Image segmentation based on gray stretch and threshold algorithm. Optik - International Journal for Light and Electron Optics 126(6):626–629

    Article  Google Scholar 

  45. Chang CC, Hsiao JY, Hsieh CP (2008) An adaptive median filter for image denoising. In: Proceeding of the Second International Symposium on Intelligent Information Technology Application, vol 2, pp 346–350

  46. Zhou L, Wu D, Dong Z, Li X (2017) When collaboration hugs intelligence: Content delivery over ultra-dense networks. IEEE Commun Mag 55(12):91–95

    Article  Google Scholar 

  47. Liang Z, Wu D, Chen J, Dong Z (2018) Greening the smart cities Energy-efficient massive content delivery via d2d communications. IEEE Trans Ind Inf 14(4):1626–1634

    Article  Google Scholar 

  48. Yuan X, José-Fernán M, Martina E, Lourdes LS (2016) An improved otsu threshold segmentation method for underwater simultaneous localization and mapping-based navigation. Sensors 16(7):1148

    Article  Google Scholar 

  49. Zhou Y, Gu X, Wu D, Chen M, Chan TH, Ho SW (2018) Statistical study of view preferences for online videos with cross-platform information. IEEE Trans Multimedia 20(6):1512–1524

    Article  Google Scholar 

  50. Zhang YJ (1996) A survey on evaluation methods for image segmentation. Pattern Recogn 29(8):1335–1346

    Article  Google Scholar 

  51. Unnikrishnan R, Pantofaru C, Hebert M (2007) Toward objective evaluation of image segmentation algorithms. IEEE Trans Pattern Anal Mach Intell 29(6):929–944

    Article  Google Scholar 

  52. Schimpf MO, Gottenger EE, Wagner JR (2008) Universal ureteral stent placement at hysterectomy to identify ureteral injury: a decision analysis. BJOG 115(9):1151–1158

    Article  Google Scholar 

  53. Chahin F, Dwivedi AJ, Paramesh A, Chau W, Agrawal S, Chahin C, Kumar A, Tootla A, Tootla F, Silva YJ (2002) The implications of lighted ureteral stenting in laparoscopic colectomy. Jsls 6(1):49–52

    Google Scholar 

  54. Chen M, Shi X, Zhang Y, Wu D, Guizani M (2017) Deep features learning for medical image analysis with convolutional autoencoder neural network. IEEE Transactions on Big Data, https://doi.org/10.1109/TBDATA.2017.2717439

  55. Chen M, Zhang Y, Qiu M, Guizani N, Hao Y (2018) Spha: Smart personal health advisor based on deep analytics. IEEE Commun 56(3):164–169

    Article  Google Scholar 

  56. Chen M, Ma Y, Li Y, Wu D, Zhang Y, Youn CH (2017) Wearable 2.0: Enabling human-cloud integration in next generation healthcare systems. IEEE Commun Mag 55(1):54–61

    Article  Google Scholar 

  57. Chen M, Hao Y, Kai H, Wang L, Wang L (2017) Disease prediction by machine learning over big data from healthcare communities. IEEE Access 5(99):8869–8879

    Article  Google Scholar 

  58. Chen Min, Yang J, Zhou J, Hao Y, Zhang J, Youn CH (2018) 5g-smart diabetes: Toward personalized diabetes diagnosis with healthcare big data clouds. IEEE Commun Mag 56(4):16–23

    Article  Google Scholar 

  59. Chen M, Qian Y, Chen J, Kai H, Mao S, Hu L (2016) Privacy protection and intrusion avoidance for cloudlet-based medical data sharing. IEEE Transactions on Cloud Computing, https://doi.org/10.1109/TCC.2016.2617382

  60. Ji W, Chen Y, Chen M, Chen BW, Chen Y, Kung SY (2016) Profit maximization through online advertising scheduling for a wireless video broadcast network. IEEE Trans Mob Comput 15(8):2064–2079

    Article  Google Scholar 

  61. Ji W, Li Z, Chen Y (2012) Joint source-channel coding and optimization for layered video broadcasting to heterogeneous devices. IEEE Trans Multimedia 14(2):443–455

    Article  Google Scholar 

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Acknowledgment

This work was supported by National Key R & D Program of China, No. 2017YFC0112804, National Natural Science Foundation of China under grant project No.61370179, the Fundamental Research Funds for the Central Universities, HUST: 2016YXZD018 and HUST: 2017JYCX038, and Clinical Medicine Science and Technology Projects in Jiangsu province, No. BL2014056.

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Correspondence to Hong Liu.

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Song, E., Yu, F., Li, Y. et al. An Image-guided Endoscope System for the Ureter Detection. Mobile Netw Appl 23, 1655–1668 (2018). https://doi.org/10.1007/s11036-018-1114-z

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