Mini-DDSM [Elektronisk resurs] Mammography-based Automatic Age Estimation
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Lekamlage, Charitha Dissanayake (författare)
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3rd International Conference on Digital Medicine and Image Processing, DMIP 2020, Virtual, Online, Japan, 6 November 2020 through 9 November 2020
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Afzal, Fabia (författare)
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Westerberg, Erik (författare)
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Cheddad, Abbas (författare)
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Blekinge Tekniska Högskola (utgivare)
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Blekinge Tekniska Högskola Fakulteten för datavetenskaper (utgivare)
- Publicerad: Association for Computing Machinery, 2020
- Engelska.
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Ingår i: ACM International Conference Proceeding Series. ; 1-6
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- Relaterad länk:
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http://www.bth.se/ (Värdpublikation)
Sammanfattning
Ämnesord
Stäng
- Age estimation has attracted attention for its various medical applications. There are many studies on human age estimation from biomedical images. However, there is no research done on mammograms for age estimation, as far as we know. The purpose of this study is to devise an AI-based model for estimating age from mammogram images. Due to lack of public mammography data sets that have the age attribute, we resort to using a web crawler to download thumbnail mammographic images and their age fields from the public data set; the Digital Database for Screening Mammography. The original images in this data set unfortunately can only be retrieved by a software which is broken. Subsequently, we extracted deep learning features from the collected data set, by which we built a model using Random Forests regressor to estimate the age automatically. The performance assessment was measured using the mean absolute error values. The average error value out of 10 tests on random selection of samples was around 8 years. In this paper, we show the merits of this approach to fill up missing age values. We ran logistic and linear regression models on another independent data set to further validate the advantage of our proposed work. This paper also introduces the free-access Mini-DDSM data set. © 2020 ACM.
Ämnesord
- Engineering and Technology (hsv)
- Medical Engineering (hsv)
- Medical Image Processing (hsv)
- Teknik och teknologier (hsv)
- Medicinteknik (hsv)
- Medicinsk bildbehandling (hsv)
- Natural Sciences (hsv)
- Computer and Information Sciences (hsv)
- Computer Vision and Robotics (Autonomous Systems) (hsv)
- Naturvetenskap (hsv)
- Data- och informationsvetenskap (hsv)
- Datorseende och robotik (autonoma system) (hsv)
- Medical and Health Sciences (hsv)
- Clinical Medicine (hsv)
- Cancer and Oncology (hsv)
- Medicin och hälsovetenskap (hsv)
- Klinisk medicin (hsv)
- Cancer och onkologi (hsv)
Genre
- government publication (marcgt)
Indexterm och SAB-rubrik
- Age estimation
- Applied machine learning
- Deep learning
- Feature extraction
- Image segmentation
- Mammograms
- Regression analysis
- Decision trees
- Logistic regression
- Mammography
- Medical applications
- Web crawler
- X ray screens
- Biomedical images
- Digital database for screening mammographies
- Human age estimation
- Linear regression models
- Mammogram images
- Mammographic images
- Mean absolute error
- Performance assessment
- Medical image processing
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