20.14.1 Medical Applications -- Gastrointestinal Tract, Gastric Images

Chapter Contents (Back)
Gastrointestinal. Endoscopic Imaging.

Martinez-Herrera, S.E.[Sergio E.], Benezeth, Y.[Yannick], Boffety, M.[Matthieu], Emile, J.F.[Jean-Franšois], Marzani, F.[Franck], Lamarque, D.[Dominique], Goudail, F.[Franšois],
Identification of precancerous lesions by multispectral gastroendoscopy,
SIViP(10), No. 3, March 2016, pp. 455-462.
Springer DOI 1602
BibRef

Iakovidis, D.K., Georgakopoulos, S.V., Vasilakakis, M., Koulaouzidis, A., Plagianakos, V.P.,
Detecting and Locating Gastrointestinal Anomalies Using Deep Learning and Iterative Cluster Unification,
MedImg(37), No. 10, October 2018, pp. 2196-2210.
IEEE DOI 1810
Feature extraction, Training, Lesions, Image segmentation, Image color analysis, Endoscopes, Gastrointestinal tract, machine learning BibRef

Wang, X., Seetohul, V., Chen, R., Zhang, Z., Qian, M., Shi, Z., Yang, G., Mu, P., Wang, C., Huang, Z., Zhou, Q., Zheng, H., Cochran, S., Qiu, W.,
Development of a Mechanical Scanning Device With High-Frequency Ultrasound Transducer for Ultrasonic Capsule Endoscopy,
MedImg(36), No. 9, September 2017, pp. 1922-1929.
IEEE DOI 1709
biomedical ultrasonics, endoscopes, gastrointestinaltract, BibRef

Li, G., Li, H., Duan, X., Zhou, Q., Zhou, J., Oldham, K.R., Wang, T.D.,
Visualizing Epithelial Expression in Vertical and Horizontal Planes With Dual Axes Confocal Endomicroscope Using Compact Distal Scanner,
MedImg(36), No. 7, July 2017, pp. 1482-1490.
IEEE DOI 1707
Biomedical optical imaging, Micromechanical devices, Mirrors, Optical device fabrication, Optical imaging, Optical scattering, Molecular and cellular imaging, endoscopy, gastrointestinal tract, optical imaging, system, design BibRef

Khan, M.A.[Mehshan Ahmed], Khan, M.A.[Muhammad Attique], Ahmed, F.[Fawad], Mittal, M.[Mamta], Goyal, L.M.[Lalit Mohan], Hemanth, D.J.[D. Jude], Satapathy, S.C.[Suresh Chandra],
Gastrointestinal diseases segmentation and classification based on duo-deep architectures,
PRL(131), 2020, pp. 193-204.
Elsevier DOI 2004
Stomach diseases, Mask RCNN, CNN features, Feature selection BibRef

Li, G., Duan, X., Lee, M., Birla, M., Chen, J., Oldham, K.R., Wang, T.D., Li, H.,
Ultra-Compact Microsystems-Based Confocal Endomicroscope,
MedImg(39), No. 7, July 2020, pp. 2406-2414.
IEEE DOI 2007
Mirrors, Instruments, Endoscopes, Micromechanical devices, Imaging, Optical fibers, Optical imaging, endoscopy, system design, gastrointestinal tract BibRef

Yang, S., Lemke, C., Cox, B.F., Newton, I.P., Nńthke, I., Cochran, S.,
A Learning-Based Microultrasound System for the Detection of Inflammation of the Gastrointestinal Tract,
MedImg(40), No. 1, January 2021, pp. 38-47.
IEEE DOI 2012
Machine learning, Mice, Diseases, Acoustics, Imaging, Endoscopes, Gastrointestinal tract, Computer-aided detection and diagnosis, neural network BibRef

Hu, H.Y.[Hui-Yi], Zheng, W.F.[Wen-Fang], Zhang, X.[Xu], Zhang, X.S.[Xin-Sen], Liu, J.Q.[Ji-Quan], Hu, W.L.[Wei-Ling], Duan, H.L.[Hui-Long], Si, J.M.[Jian-Min],
Content-Based Gastric Image Retrieval Using Convolutional Neural Networks,
IJIST(31), No. 1, 2021, pp. 439-449.
DOI Link 2102
clinical aided diagnosis, content-based image retrieval, convolutional neural networks, gastric precancerous diseases, gastric-map BibRef

Wang, L.S.[Lian-Sheng], Jiao, Y.[Yudi], Qiao, Y.[Ying], Zeng, N.[Nianyin], Yu, R.[Rongshan],
A novel approach combined transfer learning and deep learning to predict TMB from histology image,
PRL(135), 2020, pp. 244-248.
Elsevier DOI 2006
Gastrointestinal cancer, Tumor mutational burden, Deep learning, Pathological images BibRef

Mathialagan, P.[Prabhakaran], Chidambaranathan, M.[Malathy],
Computer vision techniques for Upper Aero-Digestive Tract tumor grading classification: Addressing pathological challenges,
PRL(144), 2021, pp. 42-53.
Elsevier DOI 2103
FR-PSO, SVM, Classification, Cancer, UADT, Machine Learning BibRef


Jha, D.[Debesh], Ali, S.[Sharib], Emanuelsen, K.[Krister], Hicks, S.A.[Steven A.], Thambawita, V.[Vajira], Garcia-Ceja, E.[Enrique], Riegler, M.A.[Michael A.], de Lange, T.[Thomas], Schmidt, P.T.[Peter T.], Johansen, H.D.[Hňvard D.], Johansen, D.[Dag], Halvorsne, P.[Pňl],
Kvasir-instrument: Diagnostic and Therapeutic Tool Segmentation Dataset in Gastrointestinal Endoscopy,
MMMod21(II:218-229).
Springer DOI 2106
BibRef

Studer, L.[Linda], Wallau, J.[Jannis], Dawson, H.[Heather], Zlobec, I.[Inti], Fischer, A.[Andreas],
Classification of Intestinal Gland Cell-Graphs Using Graph Neural Networks,
ICPR21(3636-3643)
IEEE DOI 2105
Deep learning, Message passing, Glands, Morphology, Graph neural networks, Pattern recognition, Mirrors BibRef

Chheda, T.[Tejas], Iyer, R.[Rithvika], Koppaka, S.[Soumya], Kalbande, D.[Dhananjay],
Gastrointestinal Tract Anomaly Detection from Endoscopic Videos Using Object Detection Approach,
ISVC20(II:494-505).
Springer DOI 2103
BibRef

He, Q.[Qi], Bano, S.[Sophia], Stoyanov, D.[Danail], Zuo, S.[Siyang],
Hybrid Loss with Network Trimming for Disease Recognition in Gastrointestinal Endoscopy,
EndoTect20(299-306).
Springer DOI 2103
BibRef

Galdran, A.[Adrian], Carneiro, G.[Gustavo], Ballester, M.A.G.[Miguel A. Gonzßlez],
A Hierarchical Multi-task Approach to Gastrointestinal Image Analysis,
EndoTect20(275-282).
Springer DOI 2103
BibRef

Togo, R., Ogawa, T., Haseyama, M.,
Multimodal Image-to-Image Translation for Generation of Gastritis Images,
ICIP20(2466-2470)
IEEE DOI 2011
Cancer, Inspection, Blood, X-ray imaging, Task analysis, Indexes, Image-to-image translation, gastritis BibRef

Togo, R., Ishihara, K., Ogawa, T., Haseyama, M.,
Anonymous Gastritis Image Generation via Adversarial Learning from Gastric X-Ray Images,
ICIP18(2082-2086)
IEEE DOI 1809
X-ray imaging, Biomedical imaging, Image recognition, Stomach, Generative adversarial networks, gastritis BibRef

Li, G., Togo, R., Ogawa, T., Haseyama, M.,
Soft-Label Anonymous Gastric X-Ray Image Distillation,
ICIP20(305-309)
IEEE DOI 2011
X-ray imaging, Medical diagnostic imaging, Training, Stomach, Data privacy, Image coding, Medical image distillation, gastric X-ray images BibRef

Kanai, M., Togo, R., Ogawa, T., Haseyama, M.,
Gastritis Detection from Gastric X-Ray Images Via Fine-Tuning of Patch-Based Deep Convolutional Neural Network,
ICIP19(1371-1375)
IEEE DOI 1910
Gastritis detection, convolutional neural network, fine-tuning, gastric X-ray images BibRef

Ishihara, K.[Kenta], Ogawa, T.[Takahiro], Haseyama, M.[Miki],
Detection of gastric cancer risk from X-ray images via patch-based convolutional neural network,
ICIP17(2055-2059)
IEEE DOI 1803
BibRef
Earlier:
Helicobacter pylori infection detection from multiple x-ray images based on combination use of support vector machine and multiple kernel learning,
ICIP15(4728-4732)
IEEE DOI 1512
BibRef
Earlier:
Helicobacter pylori infection detection from multiple X-ray images based on decision level fusion,
ICIP14(2769-2773)
IEEE DOI 1502
Biomedical imaging, Cancer, Endoscopes, Feature extraction, Support vector machines, Training, X-ray imaging, Bag-of-Features, gastric cancer risk detection. Helicobacter pylori. Cancer BibRef

Trinh, D.H., Daul, C., Blondel, W., Lamarque, D.,
Mosaicing of Images with Few Textures and Strong Illumination Changes: Application to Gastroscopic Scenes,
ICIP18(1263-1267)
IEEE DOI 1809
Lighting, Robustness, Image color analysis, Image sequences, Estimation, Stomach, Kernel, Image mosaicing, Medical endoscopy BibRef

Diamantis, D., Iakovidis, D.K., Koulaouzidis, A.,
Investigating Cross-Dataset Abnormality Detection in Endoscopy with A Weakly-Supervised Multiscale Convolutional Neural Network,
ICIP18(3124-3128)
IEEE DOI 1809
Feature extraction, Computer architecture, Training, Endoscopes, Neurons, Convolutional neural networks, Gastrointestinal tract, multiscale image analysis BibRef

Vu, H.[Hai], Echigo, T.[Tomio], Imura, Y.[Yuma], Yanagawa, Y.[Yukiko], Yagi, Y.S.[Yasu-Shi],
Segmenting Reddish Lesions in Capsule Endoscopy Images Using a Gastrointestinal Color Space,
ICPR14(3263-3268)
IEEE DOI 1412
Educational institutions BibRef

Minami, Y.[Yoshitaka], Ohnishi, T.[Takashi], Kawahira, H.[Hiroshi], Haneishi, H.[Hideaki],
Fundamental Study on Intraoperative Quantification of Gastrointestinal Viability by Transmission Light Intensity Analysis,
ICISP14(72-78).
Springer DOI 1406
BibRef

Martinez-Herrera, S.E.[Sergio E.], Benezeth, Y.[Yannick], Boffety, M.[Matthieu], Emile, J.F.[Jean-Franšois], Marzani, F.[Franck], Lamarque, D.[Dominique], Goudail, F.[Franšois],
Multispectral Endoscopy to Identify Precancerous Lesions in Gastric Mucosa,
ICISP14(43-51).
Springer DOI 1406
BibRef

Kim, K.B.[Kwang-Baek], Kim, S.S.[Sung-Shin], Kim, G.H.[Gwang-Ha],
Analysis System of Endoscopic Image of Early Gastric Cancer,
ICIAR06(II: 547-558).
Springer DOI 0610
BibRef

Chapter on Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models continues in
Medical Applications -- Colonoscopy, Colon Cancer .


Last update:Sep 19, 2021 at 21:11:01