Maffeis, G;
Pifferi, A;
Dalla Mora, A;
Di Sieno, L;
Cubeddu, R;
Tosi, A;
Conca, E;
... Taroni, Paola; + view all
(2023)
Breast lesion classification based on absorption and composition parameters: a look at SOLUS first outcomes.
In: Fantini, Sergio and Taroni, Paola, (eds.)
Optical Tomography and Spectroscopy of Tissue XV.
SPIE BIOS: San Francisco, California, United States.
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Abstract
A machine learning classification algorithm is applied to the SOLUS database to discriminate benign and malignant breast lesions, based on absorption and composition properties retrieved through diffuse optical tomography. The Mann-Whitney test indicates oxy-hemoglobin (p-value = 0.0007) and lipids (0.0387) as the most significant constituents for lesion classification, but work is in progress for further analysis. Together with sensitivity (91%), specificity (75%) and the Area Under the ROC Curve (0.83), special metrics for imbalanced datasets (27% of malignant lesions) are applied to the machine learning outcome: balanced accuracy (83%) and Matthews Correlation Coefficient (0.65). The initial results underline the promising informative content of optical data.
| Type: | Proceedings paper |
|---|---|
| Title: | Breast lesion classification based on absorption and composition parameters: a look at SOLUS first outcomes |
| Event: | SPIE Photonics West BiOS |
| Dates: | 28 Jan 2023 - 3 Feb 2023 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1117/12.2648945 |
| Publisher version: | https://doi.org/10.1117/12.2648945 |
| Language: | English |
| Additional information: | This version is the version of record. For information on re-use, please refer to the publisher’s terms and conditions |
| Keywords: | Breast, Absorption, Machine learning, Data analysis, Diffuse optical imaging, Diffuse optical tomography, Image segmentation, Breast cancer, Ultrasound transducers |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10171830 |
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