Abstract
Advances in AI allow for fake image creation. These techniques can be used to fake mammograms. This could impact patient care and medicolegal cases. One method to verify that an image is original is to confirm the source of the image. A deep-learning algorithm(DeepMammo)-based on CNNs and FCNNs, used to identify the machine that created any mammogram. We analyze mammograms of 1574 patients obtained on 7-different mammography machines and randomly split the dataset by patient into training/validation(80%) and test(20%) datasets. DeepMammo has an accuracy of 98.09%, AUC of 95.96% in the test dataset.
| Original language | English (US) |
|---|---|
| Article number | 342 |
| Journal | IS and T International Symposium on Electronic Imaging Science and Technology |
| Volume | 36 |
| Issue number | 4 |
| DOIs | |
| State | Published - 2024 |
| Externally published | Yes |
| Event | IS and T International Symposium on Electronic Imaging 2024: Media Watermarking, Security, and Forensics, MWSF 2024 - San Francisco, United States Duration: Jan 21 2024 → Jan 25 2024 |
Keywords
- Deep Learning
- Forensic Science
- Machine Learning
- Mammograms
- Medical Imaging
- Radiology
ASJC Scopus subject areas
- Computer Graphics and Computer-Aided Design
- Computer Science Applications
- Human-Computer Interaction
- Software
- Electrical and Electronic Engineering
- Atomic and Molecular Physics, and Optics
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