Polyp detection in video colonoscopy using deep learning

被引：1

作者：

Luca, Mihaela ^{[1
]}

Ciobanu, Adrian ^{[1
]}

机构：

[1] Romanian Acad, Inst Comp Sci, Iasi Branch, 8 Bd Carol I, Iasi, Romania

来源：

JOURNAL OF INTELLIGENT & FUZZY SYSTEMS | 2022年 / 43卷 / 02期

关键词：

Video colonoscopy; polyp detection; deep learning; real time; COMPUTER-AIDED DIAGNOSIS; CLASSIFICATION;

D O I：

10.3233/JIFS-219276

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Video colonoscopy automatic processing is a challenge and further development of computer assisted diagnosis is very helpful in correctness assessment of the exam, in e-learning and training, for statistics on polyps' malignity or in polyps' survey. New devices and programming languages are emerging and deep learning begun already to furnish astonishing results, in the quest for high speed and optimal polyp detection software. This paper presents a successful attempt in detecting the intestinal polyps in real time video colonoscopy with deep learning, using Mobile Net.

引用

页码：1751 / 1759

页数：9

共 50 条

[1] Polyp detection using CNNs in colonoscopy video
Haj-Manouchehri, Azadeh
Mohammadi, Hossein Mahvash
[J]. IET COMPUTER VISION, 2020, 14 (05) : 241 - 247
[2] Automated Polyp Detection System in Colonoscopy using Object Detection Algorithm based on Deep Learning
Lee, Jeong-Nam
Cho, Hyun-Chong
[J]. Transactions of the Korean Institute of Electrical Engineers, 2021, 70 (01): : 152 - 157
[3] Polyp detection in colonoscopy video using elliptical shape feature
Hwang, Sae
Oh, JungHwan
Tavanapong, Wallapak
Wong, Johnny
de Groen, Piet C.
[J]. 2007 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOLS 1-7, 2007, : 1029 - +
[4] Real-Time Polyp Detection, Localization and Segmentation in Colonoscopy Using Deep Learning
Jha, Debesh
Ali, Sharib
Tomar, Nikhil Kumar
Johansen, Havard D.
Johansen, Dag
Rittscher, Jens
Riegler, Michael A.
Halvorsen, Pal
[J]. IEEE ACCESS, 2021, 9 : 40496 - 40510
[5] AUTOMATIC POLYP DETECTION IN COLONOSCOPY PROCEDURE USING DEEP LEARNING AND COMPUTER VISION TECHNIQUES
Zur, Dror
Gal, Oren
Kopelman, Yael
[J]. GASTROENTEROLOGY, 2018, 154 (06) : S35 - S36
[6] Polyp Location in Colonoscopy Based on Deep Learning
Ma, Yan
Li, Ya
Yao, Jianning
Chen, Bing
Deng, Jicai
Yang, Xiaonan
[J]. 2019 8TH INTERNATIONAL SYMPOSIUM ON NEXT GENERATION ELECTRONICS (ISNE), 2019,
[7] Polyp characterization using deep learning and a publicly accessible polyp video database
Kader, Rawen
Cid-Mejias, Anton
Brandao, Patrick
Islam, Shahraz
Hebbar, Sanjith
Puyal, Juana Gonzalez-Bueno
Ahmad, Omer F.
Hussein, Mohamed
Toth, Daniel
Mountney, Peter
Seward, Ed
Vega, Roser
Stoyanov, Danail
Lovat, Laurence B.
[J]. DIGESTIVE ENDOSCOPY, 2023, 35 (05) : 645 - 655
[8] A Prospective Validation of Deep Learning for Polyp Auto-detection during Colonoscopy
Wang, Pu
Xiao, Xiao
Liu, Jingjia
Li, Liangping
Tu, Mengtian
He, Jiong
Hu, Xiao
Xiong, Fei
Xin, Yi
Liu, Xiaogang
[J]. AMERICAN JOURNAL OF GASTROENTEROLOGY, 2017, 112 : S106 - S108
[9] Improving Automatic Polyp Detection Using CNN by Exploiting Temporal Dependency in Colonoscopy Video
Qadir, Hemin Ali
Balasingham, Ilangko
Solhusvik, Johannes
Bergsland, Jacob
Aabakken, Lars
Shin, Younghak
[J]. IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 2020, 24 (01) : 180 - 193
[10] Real-Time Polyp Detection for Colonoscopy Video on CPU
Li, Xuetong
Liu, Rui
Li, Mingzhen
Liu, Yi
Jiang, Lianghui
Zhou, Changhong
[J]. 2020 IEEE 32ND INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE (ICTAI), 2020, : 890 - 897

← 1 2 3 4 5 →