Fourier Transformation-Based Analysis of X-Ray Diffraction Pattern of Keratin for Cancer Detection
With the growing number of cancer cases and deaths around the world, fast, non-invasive, and inexpensive screening is paramount. We examine the feasibility of such cancer detection using the X-ray scattering properties of nails in the canine model. A total of 945 samples taken from 266 dogs were mea...
Saved in:
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-01-01
|
| Series: | Crystals |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-4352/15/1/57 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832588751131377664 |
|---|---|
| author | Alexander Alekseev Oleksii Avdieiev Sasha Murokh Delvin Yuk Alexander Lazarev Daizie Labelle Lev Mourokh Pavel Lazarev |
| author_facet | Alexander Alekseev Oleksii Avdieiev Sasha Murokh Delvin Yuk Alexander Lazarev Daizie Labelle Lev Mourokh Pavel Lazarev |
| author_sort | Alexander Alekseev |
| collection | DOAJ |
| description | With the growing number of cancer cases and deaths around the world, fast, non-invasive, and inexpensive screening is paramount. We examine the feasibility of such cancer detection using the X-ray scattering properties of nails in the canine model. A total of 945 samples taken from 266 dogs were measured, with 84 animals diagnosed with cancer. To analyze the obtained X-ray diffraction patterns of keratin, we propose a method based on the two-dimensional Fourier transformation of the images. We compare 745 combinations of data preprocessing steps and machine learning classifiers and determine the corresponding performance metrics. Excellent classification results are demonstrated, with sensitivity or specificity achieving 100% and the best value for balanced accuracy being 87.5%. We believe that our approach can be extended to human samples to develop a non-invasive, convenient, and cheap method for early cancer detection. |
| format | Article |
| id | doaj-art-29d1fc9ab7ea4c5a9501dbd4cdfbf79c |
| institution | Kabale University |
| issn | 2073-4352 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Crystals |
| spelling | doaj-art-29d1fc9ab7ea4c5a9501dbd4cdfbf79c2025-01-24T13:28:09ZengMDPI AGCrystals2073-43522025-01-011515710.3390/cryst15010057Fourier Transformation-Based Analysis of X-Ray Diffraction Pattern of Keratin for Cancer DetectionAlexander Alekseev0Oleksii Avdieiev1Sasha Murokh2Delvin Yuk3Alexander Lazarev4Daizie Labelle5Lev Mourokh6Pavel Lazarev7Matur UK Ltd., 5 New Street Square, London EC4A 3TW, UKMatur UK Ltd., 5 New Street Square, London EC4A 3TW, UKMatur UK Ltd., 5 New Street Square, London EC4A 3TW, UKArion Diagnostics, Inc., 911 Mustang Ct, Petaluma, CA 94954, USAArion Diagnostics, Inc., 911 Mustang Ct, Petaluma, CA 94954, USAArion Diagnostics, Inc., 911 Mustang Ct, Petaluma, CA 94954, USAArion Diagnostics, Inc., 911 Mustang Ct, Petaluma, CA 94954, USAMatur UK Ltd., 5 New Street Square, London EC4A 3TW, UKWith the growing number of cancer cases and deaths around the world, fast, non-invasive, and inexpensive screening is paramount. We examine the feasibility of such cancer detection using the X-ray scattering properties of nails in the canine model. A total of 945 samples taken from 266 dogs were measured, with 84 animals diagnosed with cancer. To analyze the obtained X-ray diffraction patterns of keratin, we propose a method based on the two-dimensional Fourier transformation of the images. We compare 745 combinations of data preprocessing steps and machine learning classifiers and determine the corresponding performance metrics. Excellent classification results are demonstrated, with sensitivity or specificity achieving 100% and the best value for balanced accuracy being 87.5%. We believe that our approach can be extended to human samples to develop a non-invasive, convenient, and cheap method for early cancer detection.https://www.mdpi.com/2073-4352/15/1/57X-ray diffractionvitacrystallographycancer detectioncanine modelkeratinmachine learning |
| spellingShingle | Alexander Alekseev Oleksii Avdieiev Sasha Murokh Delvin Yuk Alexander Lazarev Daizie Labelle Lev Mourokh Pavel Lazarev Fourier Transformation-Based Analysis of X-Ray Diffraction Pattern of Keratin for Cancer Detection Crystals X-ray diffraction vitacrystallography cancer detection canine model keratin machine learning |
| title | Fourier Transformation-Based Analysis of X-Ray Diffraction Pattern of Keratin for Cancer Detection |
| title_full | Fourier Transformation-Based Analysis of X-Ray Diffraction Pattern of Keratin for Cancer Detection |
| title_fullStr | Fourier Transformation-Based Analysis of X-Ray Diffraction Pattern of Keratin for Cancer Detection |
| title_full_unstemmed | Fourier Transformation-Based Analysis of X-Ray Diffraction Pattern of Keratin for Cancer Detection |
| title_short | Fourier Transformation-Based Analysis of X-Ray Diffraction Pattern of Keratin for Cancer Detection |
| title_sort | fourier transformation based analysis of x ray diffraction pattern of keratin for cancer detection |
| topic | X-ray diffraction vitacrystallography cancer detection canine model keratin machine learning |
| url | https://www.mdpi.com/2073-4352/15/1/57 |
| work_keys_str_mv | AT alexanderalekseev fouriertransformationbasedanalysisofxraydiffractionpatternofkeratinforcancerdetection AT oleksiiavdieiev fouriertransformationbasedanalysisofxraydiffractionpatternofkeratinforcancerdetection AT sashamurokh fouriertransformationbasedanalysisofxraydiffractionpatternofkeratinforcancerdetection AT delvinyuk fouriertransformationbasedanalysisofxraydiffractionpatternofkeratinforcancerdetection AT alexanderlazarev fouriertransformationbasedanalysisofxraydiffractionpatternofkeratinforcancerdetection AT daizielabelle fouriertransformationbasedanalysisofxraydiffractionpatternofkeratinforcancerdetection AT levmourokh fouriertransformationbasedanalysisofxraydiffractionpatternofkeratinforcancerdetection AT pavellazarev fouriertransformationbasedanalysisofxraydiffractionpatternofkeratinforcancerdetection |