Discrete Wavelet Coefficient-based Embeddable Branch for Ultrasound Breast Masses Classification
Abstract
References
Index Terms
- Discrete Wavelet Coefficient-based Embeddable Branch for Ultrasound Breast Masses Classification
Recommendations
Classifying breast masses in volumetric whole breast ultrasound data: a 2.5-dimensional approach
IWDM'10: Proceedings of the 10th international conference on Digital MammographyThe aim of this paper is to investigate a 2.5-dimensional approach in classifying masses as benign or malignant in volumetric anisotropic voxel whole breast ultrasound data In this paper, the term 2.5-dimensional refers to the use of a series of 2-...
Breast cancer masses classification using deep convolutional neural networks and transfer learning
AbstractWith the recent advances in the deep learning field, the use of deep convolutional neural networks (DCNNs) in biomedical image processing becomes very encouraging. This paper presents a new classification model for breast cancer masses based on ...
Deep learning-based segmentation of breast masses in dedicated breast CT imaging: Radiomic feature stability between radiologists and artificial intelligence
AbstractA deep learning (DL) network for 2D-based breast mass segmentation in unenhanced dedicated breast CT images was developed and validated, and its robustness in radiomic feature stability and diagnostic performance compared to manual ...
Highlights- The validity of engineered solutions for breast mass segmentation is investigated in the perspective of radiomic analyses.
Comments
Information & Contributors
Information
Published In
- Conference Chairs:
- Jiman Hong,
- Maart Lanperne,
- Program Chairs:
- Juw Won Park,
- Tomas Cerny,
- Publication Chair:
- Hossain Shahriar
Sponsors
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Check for updates
Author Tags
Qualifiers
- Research-article
Conference
Acceptance Rates
Upcoming Conference
- Sponsor:
- sigapp
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 27Total Downloads
- Downloads (Last 12 months)12
- Downloads (Last 6 weeks)0
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in