Skip to main content
Top

2021 | OriginalPaper | Chapter

10. AI in the Detection and Analysis of Colorectal Lesions Using Colonoscopy

Authors : Zhe Guo, Xin Zhu, Daiki Nemoto, Kazunori Togashi

Published in: Advances in Artificial Intelligence, Computation, and Data Science

Publisher: Springer International Publishing

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Figure 10.1 illustrates the organization of this chapter. We begin with a brief review of colon anatomy and an overview of general information on colorectal cancers (CRCs). In Sect. 1.2, we introduce the details of colonoscopy, the most important tool for the screening, diagnosis, and therapy of CRCs.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literature
1.
go back to reference Torre LA, Bray F, Siegel RL, Ferlay J, Lortet-tieulent J, Jemal A (2015) Global cancer statistics, 2012. CA Cancer J Clin 65:87–108PubMed Torre LA, Bray F, Siegel RL, Ferlay J, Lortet-tieulent J, Jemal A (2015) Global cancer statistics, 2012. CA Cancer J Clin 65:87–108PubMed
2.
go back to reference Siegel R, DeSantis C, Jemal A (2014). Colorectal cancer statistics, 2014. CA: Cancer J Clinicians 64(2):104–117 Siegel R, DeSantis C, Jemal A (2014). Colorectal cancer statistics, 2014. CA: Cancer J Clinicians 64(2):104–117
3.
go back to reference Chen W, Zheng R, Baade PD, Zhang S, Zeng H, Bray F, He J (2016). Cancer statistics in China, 2015. CA: Cancer J clinicians 66(2):115–132 Chen W, Zheng R, Baade PD, Zhang S, Zeng H, Bray F, He J (2016). Cancer statistics in China, 2015. CA: Cancer J clinicians 66(2):115–132
4.
go back to reference Pickhardt PJ (2016) Emerging stool-based and blood-based non-invasive DNA tests for colorectal cancer screening: the importance of cancer prevention in addition to cancer detection. Abdominal Radiol 41(8):1441–1444 Pickhardt PJ (2016) Emerging stool-based and blood-based non-invasive DNA tests for colorectal cancer screening: the importance of cancer prevention in addition to cancer detection. Abdominal Radiol 41(8):1441–1444
6.
go back to reference Meyer JE, Narang T, Schnoll Sussman FH, Pochapin MB, Christos PJ, Sherr DL (2010) Increasing incidence of rectal cancer in patients aged younger than 40 years. Cancer 116(18):4354–4359PubMed Meyer JE, Narang T, Schnoll Sussman FH, Pochapin MB, Christos PJ, Sherr DL (2010) Increasing incidence of rectal cancer in patients aged younger than 40 years. Cancer 116(18):4354–4359PubMed
7.
go back to reference Gado A, Ebeid B, Abdelmohsen A, Axon A (2014) Colorectal cancer in Egypt is commoner in young people: Is this cause for alarm? Alexandria J Med 50(3):197–201 Gado A, Ebeid B, Abdelmohsen A, Axon A (2014) Colorectal cancer in Egypt is commoner in young people: Is this cause for alarm? Alexandria J Med 50(3):197–201
8.
go back to reference Winawer SJ, Zauber AG, Ho MN, et al (1993) Prevention of colorectal cancer by colonoscopic polypectomy. The National Polyp Study Workgroup. N Engl J Med 329:1977–81 Winawer SJ, Zauber AG, Ho MN, et al (1993) Prevention of colorectal cancer by colonoscopic polypectomy. The National Polyp Study Workgroup. N Engl J Med 329:1977–81
9.
go back to reference Zauber AG, Winawer SJ, O’Brien MJ et al (2012) Colonoscopic polypectomy and long-term prevention of colorectal-cancer deaths. N Engl J Med 366:687–696PubMedPubMedCentral Zauber AG, Winawer SJ, O’Brien MJ et al (2012) Colonoscopic polypectomy and long-term prevention of colorectal-cancer deaths. N Engl J Med 366:687–696PubMedPubMedCentral
10.
go back to reference Jess T, Gamborg M, Matzen P et al (2005) Increased risk of intestinal cancer in Crohn’s disease: a meta-analysis of population-based cohort studies[J]. Am J Gastroenterol 100(12):2724–2729PubMed Jess T, Gamborg M, Matzen P et al (2005) Increased risk of intestinal cancer in Crohn’s disease: a meta-analysis of population-based cohort studies[J]. Am J Gastroenterol 100(12):2724–2729PubMed
11.
go back to reference Agrawal S, Bhupinderjit A, Bhutani MS et al (2005) Colorectal cancer in african americans[J]. Am J Gastroenterol 100(3):515–523PubMed Agrawal S, Bhupinderjit A, Bhutani MS et al (2005) Colorectal cancer in african americans[J]. Am J Gastroenterol 100(3):515–523PubMed
12.
go back to reference Khan N, Afaq F, Mukhtar H (2010) Lifestyle as risk factor for cancer: Evidence from human studies[J]. Cancer Lett 293(2):133–143PubMedPubMedCentral Khan N, Afaq F, Mukhtar H (2010) Lifestyle as risk factor for cancer: Evidence from human studies[J]. Cancer Lett 293(2):133–143PubMedPubMedCentral
13.
go back to reference Baena R, Salinas P (2015) Diet and colorectal cancer[J]. Maturitas 80(3):258–264PubMed Baena R, Salinas P (2015) Diet and colorectal cancer[J]. Maturitas 80(3):258–264PubMed
14.
go back to reference Amin M, Edge SB, Greene FL et al (2017) AJCC Cancer Staging Manual, 8th ed. Switzerland, Springer Amin M, Edge SB, Greene FL et al (2017) AJCC Cancer Staging Manual, 8th ed. Switzerland, Springer
15.
go back to reference Sonnenberg A, Amorosi SL, Lacey MJ et al (2008) Patterns of endoscopy in the united states: analysis of data from the centers for medicare and medicaid services and the national endoscopic database. Gastrointest Endosc 67:489–496PubMed Sonnenberg A, Amorosi SL, Lacey MJ et al (2008) Patterns of endoscopy in the united states: analysis of data from the centers for medicare and medicaid services and the national endoscopic database. Gastrointest Endosc 67:489–496PubMed
16.
go back to reference Siegel R, Desantis C, Jemal A (2014) Colorectal Cancer Statistics, 2014. CA Cancer J Clin 64:104–117PubMed Siegel R, Desantis C, Jemal A (2014) Colorectal Cancer Statistics, 2014. CA Cancer J Clin 64:104–117PubMed
17.
go back to reference Gupta N, Bansal A, Rao D, Early DS, Jonnalagadda S, Wani SB, et al (2012) Prevalence of advanced histological features in diminutive and small colon polyps. Gastrointest Endosc 75(5):1022–30 Gupta N, Bansal A, Rao D, Early DS, Jonnalagadda S, Wani SB, et al (2012) Prevalence of advanced histological features in diminutive and small colon polyps. Gastrointest Endosc 75(5):1022–30
18.
go back to reference Lieberman D, Moravec M, Holub J, Michaels L, Eisen G (2008) Polyp size and advanced histology in patients un- dergoing colonoscopy screening: implications for CT colonography. Gastroenterology 135(4):1100–1105PubMed Lieberman D, Moravec M, Holub J, Michaels L, Eisen G (2008) Polyp size and advanced histology in patients un- dergoing colonoscopy screening: implications for CT colonography. Gastroenterology 135(4):1100–1105PubMed
19.
go back to reference Esteva A, Kuprel B, Novoa RA et al (2017) Dermatologist-level classification of skin cancer with deep neural networks. Nature 542:115–118PubMedPubMedCentral Esteva A, Kuprel B, Novoa RA et al (2017) Dermatologist-level classification of skin cancer with deep neural networks. Nature 542:115–118PubMedPubMedCentral
20.
go back to reference Ehteshami Bejnordi B, Veta M, Johannes van Diest P, et al (2017) Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer. JAMA 318: 2199–210 Ehteshami Bejnordi B, Veta M, Johannes van Diest P, et al (2017) Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer. JAMA 318: 2199–210
21.
go back to reference Ahn SB, Han DS, Bae JH et al (2012) The miss rate for colorectal adenoma determined by quality-adjusted, back-to-back colono- scopies. Gut Liv 6:64–70 Ahn SB, Han DS, Bae JH et al (2012) The miss rate for colorectal adenoma determined by quality-adjusted, back-to-back colono- scopies. Gut Liv 6:64–70
22.
go back to reference Stoffel EM, Turgeon DK, Stockwell DH et al (2008) Chromoen- doscopy detects more adenomas than colonoscopy using intensive inspection without dye spraying. Cancer Prev Res (Phila) 1:507–13 Stoffel EM, Turgeon DK, Stockwell DH et al (2008) Chromoen- doscopy detects more adenomas than colonoscopy using intensive inspection without dye spraying. Cancer Prev Res (Phila) 1:507–13
23.
go back to reference Castaneda D, Popov VB, Verheyen E et al (2018) New technologies improve adenoma detection rate, adenoma miss rate, and polyp detection rate: a systematic review and meta-analysis. Gas- trointest Endosc 88:209–222 Castaneda D, Popov VB, Verheyen E et al (2018) New technologies improve adenoma detection rate, adenoma miss rate, and polyp detection rate: a systematic review and meta-analysis. Gas- trointest Endosc 88:209–222
24.
go back to reference Corley DA, Jensen CD, Marks AR et al (2014) Adenoma detection rate and risk of colorectal cancer and death. N Engl J Med 370:1298–1306PubMedPubMedCentral Corley DA, Jensen CD, Marks AR et al (2014) Adenoma detection rate and risk of colorectal cancer and death. N Engl J Med 370:1298–1306PubMedPubMedCentral
25.
go back to reference Kaminski MF, Regula J, Kraszewska E et al (2010) Quality indicators for colonoscopy and the risk of interval cancer. N Engl J Med 362:1795–1803PubMed Kaminski MF, Regula J, Kraszewska E et al (2010) Quality indicators for colonoscopy and the risk of interval cancer. N Engl J Med 362:1795–1803PubMed
26.
go back to reference van Rijn JC, Reitsma JB, Stoker J et al (2006) Polyp miss rate determined by tandem colonoscopy: a systematic review. Am J Gastroenterol 101(2):343–350PubMed van Rijn JC, Reitsma JB, Stoker J et al (2006) Polyp miss rate determined by tandem colonoscopy: a systematic review. Am J Gastroenterol 101(2):343–350PubMed
27.
go back to reference Morris EJA, Rutter MD, Finan PJ, Thomas JD, Valori R (2015) Post-colonoscopy colorectal cancer (PCCRC) rates vary considerably depending on the method used to calculate them: a retrospective observational population-based study of PCCRC in the English National Health Service. Gut 64:1248–1256PubMed Morris EJA, Rutter MD, Finan PJ, Thomas JD, Valori R (2015) Post-colonoscopy colorectal cancer (PCCRC) rates vary considerably depending on the method used to calculate them: a retrospective observational population-based study of PCCRC in the English National Health Service. Gut 64:1248–1256PubMed
28.
go back to reference Le Clercq CMC, Bouwens MWE, Rondagh EJA et al (2014) Postcolonoscopy colorectal cancers are preventable: a population-based study. Gut 63:957–963PubMed Le Clercq CMC, Bouwens MWE, Rondagh EJA et al (2014) Postcolonoscopy colorectal cancers are preventable: a population-based study. Gut 63:957–963PubMed
29.
go back to reference Lee CK, Park DI, Lee SH et al (2011) Participation by experienced endoscopy nurses increases the detection rate of colon polyps during a screening colonoscopy: a multicenter, prospective, randomized study. Gastrointest Endosc 74:1094–1102PubMed Lee CK, Park DI, Lee SH et al (2011) Participation by experienced endoscopy nurses increases the detection rate of colon polyps during a screening colonoscopy: a multicenter, prospective, randomized study. Gastrointest Endosc 74:1094–1102PubMed
30.
go back to reference Zhu X, Wang Y, Nemoto D et al (2018) Identification of sessile serrated adenoma/polyp using convolutional neural network (Artificial Intelligence). Gastrointest Endosc 87:AB251 Zhu X, Wang Y, Nemoto D et al (2018) Identification of sessile serrated adenoma/polyp using convolutional neural network (Artificial Intelligence). Gastrointest Endosc 87:AB251
31.
go back to reference Misawa M, Kudo S, Mori Y et al (2018) Artificial intelligence- assisted polyp detection for colonoscopy: initial experience. Gastroenterology 154:2027–2029PubMed Misawa M, Kudo S, Mori Y et al (2018) Artificial intelligence- assisted polyp detection for colonoscopy: initial experience. Gastroenterology 154:2027–2029PubMed
32.
go back to reference Urban G, Tripathi P, Alkayali T et al (2018) Deep learning localizes and identifies polyps in real time with 96% accuracy in screening colonoscopy. Gastroenterology 155:1069–1078PubMed Urban G, Tripathi P, Alkayali T et al (2018) Deep learning localizes and identifies polyps in real time with 96% accuracy in screening colonoscopy. Gastroenterology 155:1069–1078PubMed
33.
go back to reference Wang P, Xiao X, Glissen Brown JR et al (2018) Development and validation of a deep-learning algorithm for the detection of polyps during colonoscopy. Nat Biomed Eng 2:741–748PubMed Wang P, Xiao X, Glissen Brown JR et al (2018) Development and validation of a deep-learning algorithm for the detection of polyps during colonoscopy. Nat Biomed Eng 2:741–748PubMed
34.
go back to reference Badrinarayanan V, Kendall A, Cipolla R (2017) SegNet: A deep convolutional encoder-decoder architecture for image segmentation. IEEE Trans Pattern Anal Mach Intell 39:2481–2495PubMed Badrinarayanan V, Kendall A, Cipolla R (2017) SegNet: A deep convolutional encoder-decoder architecture for image segmentation. IEEE Trans Pattern Anal Mach Intell 39:2481–2495PubMed
35.
go back to reference Wang P, Berzin TM, Glissen Brown JR et al (2019) Real-time automatic detection system increases colonoscopic polyp and adenoma detection rates: a prospective randomised controlled study. Gut 68:1813–1819PubMed Wang P, Berzin TM, Glissen Brown JR et al (2019) Real-time automatic detection system increases colonoscopic polyp and adenoma detection rates: a prospective randomised controlled study. Gut 68:1813–1819PubMed
36.
go back to reference Gupta N, Bansal A, Rao D, Early DS, Jonnalagadda S, Wani SB et al (2012) Prevalence of advanced histological features in diminutive and small colon polyps. Gastrointest Endosc 75(5):1022–1030PubMed Gupta N, Bansal A, Rao D, Early DS, Jonnalagadda S, Wani SB et al (2012) Prevalence of advanced histological features in diminutive and small colon polyps. Gastrointest Endosc 75(5):1022–1030PubMed
37.
go back to reference Guo Z, Nemoto D, Zhu X, et al. A polyp detection algorithm can detect small polyps: An ex vivo reading test compared with endoscopists[J]. Digestive Endoscopy Guo Z, Nemoto D, Zhu X, et al. A polyp detection algorithm can detect small polyps: An ex vivo reading test compared with endoscopists[J]. Digestive Endoscopy
38.
go back to reference Japanese Society for Cancer of the Colon and Rectum (2019) Japanese Classification of Colorectal, Appendiceal, and Anal Carcinoma: the 3d English Edition [Secondary Publication]. J Anus Rectum Colon 3:175–195 Japanese Society for Cancer of the Colon and Rectum (2019) Japanese Classification of Colorectal, Appendiceal, and Anal Carcinoma: the 3d English Edition [Secondary Publication]. J Anus Rectum Colon 3:175–195
39.
go back to reference Pimentel-Nunes P, Dinis-Ribeiro M, Ponchon T et al (2015) Endoscopic submucosal dissection: European Society of Gastrointestinal Endoscopy (ESGE) guideline. Endoscopy 47:829–854PubMed Pimentel-Nunes P, Dinis-Ribeiro M, Ponchon T et al (2015) Endoscopic submucosal dissection: European Society of Gastrointestinal Endoscopy (ESGE) guideline. Endoscopy 47:829–854PubMed
40.
go back to reference Draganov P, Wang A, Othman M et al (2019) AGA institute clinical practice update: endoscopic submucosal dissection in the united states. Clin Gastroenterol Hepatol 17:16–25PubMed Draganov P, Wang A, Othman M et al (2019) AGA institute clinical practice update: endoscopic submucosal dissection in the united states. Clin Gastroenterol Hepatol 17:16–25PubMed
41.
go back to reference Saitoh Y, Obara T, Watari J et al (1998) Invasion depth diagnosis of depres- sed type early colorectal cancers by combined use of videoendoscopy and chromoendoscopy. Gastrointest Endosc 48:362–370PubMed Saitoh Y, Obara T, Watari J et al (1998) Invasion depth diagnosis of depres- sed type early colorectal cancers by combined use of videoendoscopy and chromoendoscopy. Gastrointest Endosc 48:362–370PubMed
42.
go back to reference Horie H, Togashi K, Kawamura YJ et al. (2008) Colonoscopic stigmata of 1 mm or deeper submucosal invasion in colorectal cancer. Dis Colon Rectum, 1529–1534 Horie H, Togashi K, Kawamura YJ et al. (2008) Colonoscopic stigmata of 1 mm or deeper submucosal invasion in colorectal cancer. Dis Colon Rectum, 1529–1534
43.
go back to reference Ignjatovic A, East JE, Suzuki N, Vance M, Guenther T, Saunders BP (2009) Optical diagnosis of small colorectal polyps at routine colonoscopy (Detect InSpect ChAracterise Resect and Discard; DISCARD trial): a prospective cohort study. Lancet Oncol 10:1171–1178PubMed Ignjatovic A, East JE, Suzuki N, Vance M, Guenther T, Saunders BP (2009) Optical diagnosis of small colorectal polyps at routine colonoscopy (Detect InSpect ChAracterise Resect and Discard; DISCARD trial): a prospective cohort study. Lancet Oncol 10:1171–1178PubMed
44.
go back to reference Ladabaum U, Fioritto A, Mitani A et al (2013) Real-time optical biopsy of colon polyps with narrow band imaging in community practice does not yet meet key thresholds for clinical decisions. Gastroenterology 144:81–91PubMed Ladabaum U, Fioritto A, Mitani A et al (2013) Real-time optical biopsy of colon polyps with narrow band imaging in community practice does not yet meet key thresholds for clinical decisions. Gastroenterology 144:81–91PubMed
45.
go back to reference Rees CJ, Rajasekhar PT, Wilson A et al (2017) Narrow band imaging optical diagnosis of small colorectal polyps in routine clinical practice: the Detect Inspect Characterise Resect and Discard 2 (DISCARD 2) study. Gut 66:887–895PubMed Rees CJ, Rajasekhar PT, Wilson A et al (2017) Narrow band imaging optical diagnosis of small colorectal polyps in routine clinical practice: the Detect Inspect Characterise Resect and Discard 2 (DISCARD 2) study. Gut 66:887–895PubMed
46.
go back to reference Tischendorf JJW, Gross S, Winograd R et al (2010) Computer-aided classification of colorectal polyps based on vascular patterns: a pilot study. Endoscopy 42:203–207PubMed Tischendorf JJW, Gross S, Winograd R et al (2010) Computer-aided classification of colorectal polyps based on vascular patterns: a pilot study. Endoscopy 42:203–207PubMed
47.
go back to reference Gross S, Trautwein C, Behrens A et al (2011) Computer-based classification of small colorectal polyps by using narrow-band imaging with optical magnification. Gastrointest Endosc 74:1354–1359PubMed Gross S, Trautwein C, Behrens A et al (2011) Computer-based classification of small colorectal polyps by using narrow-band imaging with optical magnification. Gastrointest Endosc 74:1354–1359PubMed
48.
go back to reference Tamai N, Saito Y, Sakamoto T et al (2017) Effectiveness of computer-aided diagnosis of colorectal lesions using novel software for magnifying narrow-band imaging: a pilot study[J]. Endoscopy Int Open 5(8):E690 Tamai N, Saito Y, Sakamoto T et al (2017) Effectiveness of computer-aided diagnosis of colorectal lesions using novel software for magnifying narrow-band imaging: a pilot study[J]. Endoscopy Int Open 5(8):E690
49.
go back to reference Byrne MF, Chapados N, Soudan F et al (2019) Real-time differentiation of adenomatous and hyperplastic diminutive colorectal polyps during analysis of unaltered videos of standard colonoscopy using a deep learning model[J]. Gut 68(1):94–100PubMed Byrne MF, Chapados N, Soudan F et al (2019) Real-time differentiation of adenomatous and hyperplastic diminutive colorectal polyps during analysis of unaltered videos of standard colonoscopy using a deep learning model[J]. Gut 68(1):94–100PubMed
50.
go back to reference Chen PJ, Lin MC, Lai MJ et al (2018) Accurate classification of diminutive colorectal polyps using computer-aided analysis[J]. Gastroenterology 154(3):568–575PubMed Chen PJ, Lin MC, Lai MJ et al (2018) Accurate classification of diminutive colorectal polyps using computer-aided analysis[J]. Gastroenterology 154(3):568–575PubMed
51.
go back to reference Mori Y, Kudo S, Wakamura K et al (2015) Novel computer-aided diagnostic system for colorectal lesions by using endocytoscopy (with videos)[J]. Gastrointest Endosc 81(3):621–629PubMed Mori Y, Kudo S, Wakamura K et al (2015) Novel computer-aided diagnostic system for colorectal lesions by using endocytoscopy (with videos)[J]. Gastrointest Endosc 81(3):621–629PubMed
52.
go back to reference Misawa M, Kudo S, Mori Y, et al (2016) Characterization of colorectal lesions using a computer-aided diagnostic system for narrow-band imaging endocytoscopy[J]. Gastroenterology 150(7):1531–1532. e3 Misawa M, Kudo S, Mori Y, et al (2016) Characterization of colorectal lesions using a computer-aided diagnostic system for narrow-band imaging endocytoscopy[J]. Gastroenterology 150(7):1531–1532. e3
53.
go back to reference Mori Y, Kudo S, Chiu PWY et al (2016) Impact of an automated system for endocytoscopic diagnosis of small colorectal lesions: an international web-based study[J]. Endoscopy 48(12):1110–1118PubMed Mori Y, Kudo S, Chiu PWY et al (2016) Impact of an automated system for endocytoscopic diagnosis of small colorectal lesions: an international web-based study[J]. Endoscopy 48(12):1110–1118PubMed
54.
go back to reference Takeda K, Kudo S, Mori Y et al (2017) Accuracy of diagnosing invasive colorectal cancer using computer-aided endocytoscopy[J]. Endoscopy 49(08):798–802PubMed Takeda K, Kudo S, Mori Y et al (2017) Accuracy of diagnosing invasive colorectal cancer using computer-aided endocytoscopy[J]. Endoscopy 49(08):798–802PubMed
55.
go back to reference Mori Y, Kudo S, Misawa M et al (2018) Real-time use of artificial intelligence in identification of diminutive polyps during colonoscopy: a prospective study[J]. Ann Intern Med 169(6):357–366PubMed Mori Y, Kudo S, Misawa M et al (2018) Real-time use of artificial intelligence in identification of diminutive polyps during colonoscopy: a prospective study[J]. Ann Intern Med 169(6):357–366PubMed
56.
go back to reference Maeda Y, Kudo S, Mori Y et al (2019) Fully automated diagnostic system with artificial intelligence using endocytoscopy to identify the presence of histologic inflammation associated with ulcerative colitis (with video)[J]. Gastrointest Endosc 89(2):408–415PubMed Maeda Y, Kudo S, Mori Y et al (2019) Fully automated diagnostic system with artificial intelligence using endocytoscopy to identify the presence of histologic inflammation associated with ulcerative colitis (with video)[J]. Gastrointest Endosc 89(2):408–415PubMed
57.
go back to reference Tokunaga M, Matsumura T, Nankinzan R, et al (2020) A computer-aided diagnosis system using only white-light endoscopy for the prediction of invasion depth in colorectal cancer[J]. Gastrointest Endosc 93(3):647–653 Tokunaga M, Matsumura T, Nankinzan R, et al (2020) A computer-aided diagnosis system using only white-light endoscopy for the prediction of invasion depth in colorectal cancer[J]. Gastrointest Endosc 93(3):647–653
58.
go back to reference Nakajima Y, Zhu X, Nemoto D et al (2020) Diagnostic performance of artificial intelligence to identify deeply invasive colorectal cancer on non-magnified plain endoscopic images[J]. Endosc Int Open 8(10):E1341PubMedPubMedCentral Nakajima Y, Zhu X, Nemoto D et al (2020) Diagnostic performance of artificial intelligence to identify deeply invasive colorectal cancer on non-magnified plain endoscopic images[J]. Endosc Int Open 8(10):E1341PubMedPubMedCentral
Metadata
Title
AI in the Detection and Analysis of Colorectal Lesions Using Colonoscopy
Authors
Zhe Guo
Xin Zhu
Daiki Nemoto
Kazunori Togashi
Copyright Year
2021
DOI
https://doi.org/10.1007/978-3-030-69951-2_10

Premium Partner