Detection of abnormality in wireless capsule endoscopy images using fractal features
Published 2020 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Detection of abnormality in wireless capsule endoscopy images using fractal features
Authors
Keywords
Wireless capsule endoscopy, Anomaly detection, Fractal dimensions, Differential box-counting
Journal
COMPUTERS IN BIOLOGY AND MEDICINE
Volume 127, Issue -, Pages 104094
Publisher
Elsevier BV
Online
2020-10-28
DOI
10.1016/j.compbiomed.2020.104094
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- An EEG Database and Its Initial Benchmark Emotion Classification Performance
- (2020) Ayan Seal et al. Computational and Mathematical Methods in Medicine
- Human authentication based on fusion of thermal and visible face images
- (2019) Ayan Seal et al. MULTIMEDIA TOOLS AND APPLICATIONS
- Quantitative Texture Measurement of Gray-Scale Images: Fractal Dimension using an Improved Differential Box Counting Method
- (2019) Chinmaya Panigrahy et al. MEASUREMENT
- Fractal dimension of synthesized and natural color images in Lab space
- (2019) Chinmaya Panigrahy et al. PATTERN ANALYSIS AND APPLICATIONS
- Differential box counting methods for estimating fractal dimension of gray-scale images: A survey
- (2019) Chinmaya Panigrahy et al. CHAOS SOLITONS & FRACTALS
- Modeling uncertain data using Monte Carlo integration method for clustering
- (2019) Krishna Kumar Sharma et al. EXPERT SYSTEMS WITH APPLICATIONS
- Detecting and Locating Gastrointestinal Anomalies Using Deep Learning and Iterative Cluster Unification
- (2018) Dimitris K. Iakovidis et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- An Automatic Bleeding Frame and Region Detection Scheme for Wireless Capsule Endoscopy Videos Based on Interplane Intensity Variation Profile in Normalized RGB Color Space
- (2018) Amit Kumar Kundu et al. Journal of Healthcare Engineering
- CHOBS: Color Histogram of Block Statistics for Automatic Bleeding Detection in Wireless Capsule Endoscopy Video
- (2018) Tonmoy Ghosh et al. IEEE Journal of Translational Engineering in Health and Medicine-JTEHM
- Overfitting remedy by sparsifying regularization on fully-connected layers of CNNs
- (2018) Qi Xu et al. NEUROCOMPUTING
- PET-CT image fusion using random forest and à-trous wavelet transform
- (2017) Ayan Seal et al. International Journal for Numerical Methods in Biomedical Engineering
- Deep learning for polyp recognition in wireless capsule endoscopy images
- (2017) Yixuan Yuan et al. MEDICAL PHYSICS
- Machine Learning for Medical Imaging
- (2017) Bradley J. Erickson et al. RADIOGRAPHICS
- Human face recognition using random forest based fusion of à-trous wavelet transform coefficients from thermal and visible images
- (2016) Ayan Seal et al. AEU-INTERNATIONAL JOURNAL OF ELECTRONICS AND COMMUNICATIONS
- Improved Bag of Feature for Automatic Polyp Detection in Wireless Capsule Endoscopy Images
- (2016) Yixuan Yuan et al. IEEE Transactions on Automation Science and Engineering
- Automatic blood detection in capsule endoscopy video
- (2016) Adam Novozámský et al. JOURNAL OF BIOMEDICAL OPTICS
- Bleeding Frame and Region Detection in the Wireless Capsule Endoscopy Video
- (2016) Yixuan Yuan et al. IEEE Journal of Biomedical and Health Informatics
- An improved differential box-counting method to estimate fractal dimensions of gray-level images
- (2014) Yu Liu et al. JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION
- Optimizing lesion detection in small-bowel capsule endoscopy: from present problems to future solutions
- (2014) Anastasios Koulaouzidis et al. Expert Review of Gastroenterology & Hepatology
- Breast tumor detection in digital mammography based on extreme learning machine
- (2013) Zhiqiong Wang et al. NEUROCOMPUTING
- Computer-Aided Detection of Bleeding Regions for Capsule Endoscopy Images
- (2009) Baopu Li et al. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
- An improved box-counting method for image fractal dimension estimation
- (2009) Jian Li et al. PATTERN RECOGNITION
- Obscure bleeding detection in endoscopy images using support vector machines
- (2008) Jianguo Liu et al. OPTIMIZATION AND ENGINEERING
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreAdd your recorded webinar
Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.
Upload Now