Neutrosophic segmentation of breast lesions for dedicated breast CT

Juhun Lee, Robert M. Nishikawa, Ingrid Reiser, John M Boone

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We proposed the neutrosophic approach for segmenting breast lesions in breast Computer Tomography (bCT) images. The neutrosophic set (NS) considers the nature and properties of neutrality (or indeterminacy), which is neither true nor false. We considered the image noise as an indeterminate component, while treating the breast lesion and other breast areas as true and false components. We first transformed the image into the NS domain. Each voxel in the image can be described as its membership in True, Indeterminate, and False sets. Operations α-mean, β-enhancement, and γ-plateau iteratively smooth and contrast-enhance the image to reduce the noise level of the true set. Once the true image no longer changes, we applied one existing algorithm for bCT images, the RGI segmentation, on the resulting image to segment the breast lesions. We compared the segmentation performance of the proposed method (named as NS-RGI) to that of the regular RGI segmentation. We used a total of 122 breast lesions (44 benign, 78 malignant) of 123 non-contrasted bCT cases. We measured the segmentation performances of the NS-RGI and the RGI using the DICE coefficient. The average DICE value of the NS-RGI was 0.82 (STD: 0.09), while that of the RGI was 0.8 (STD: 0.12). The difference between the two DICE values was statistically significant (paired t test, p-value = 0.0007). We conducted a subsequent feature analysis on the resulting segmentations. The classifier performance for the NS-RGI (AUC = 0.8) improved over that of the RGI (AUC = 0.69, p-value = 0.006).

Original languageEnglish (US)
Title of host publicationMedical Imaging 2017
Subtitle of host publicationComputer-Aided Diagnosis
PublisherSPIE
Volume10134
ISBN (Electronic)9781510607132
DOIs
StatePublished - 2017
EventMedical Imaging 2017: Computer-Aided Diagnosis - Orlando, United States
Duration: Feb 13 2017Feb 16 2017

Other

OtherMedical Imaging 2017: Computer-Aided Diagnosis
CountryUnited States
CityOrlando
Period2/13/172/16/17

Fingerprint

breast
lesions
Tomography
Breast
tomography
Classifiers
Sexually Transmitted Diseases
Area Under Curve
classifiers
Noise
plateaus
augmentation
coefficients

Keywords

  • Breast CT
  • CADx
  • Neutrosophy
  • Quantitative feature analysis
  • Segmentation

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Electronic, Optical and Magnetic Materials
  • Biomaterials
  • Radiology Nuclear Medicine and imaging

Cite this

Lee, J., Nishikawa, R. M., Reiser, I., & Boone, J. M. (2017). Neutrosophic segmentation of breast lesions for dedicated breast CT. In Medical Imaging 2017: Computer-Aided Diagnosis (Vol. 10134). [101340Q] SPIE. https://doi.org/10.1117/12.2254128

Neutrosophic segmentation of breast lesions for dedicated breast CT. / Lee, Juhun; Nishikawa, Robert M.; Reiser, Ingrid; Boone, John M.

Medical Imaging 2017: Computer-Aided Diagnosis. Vol. 10134 SPIE, 2017. 101340Q.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Lee, J, Nishikawa, RM, Reiser, I & Boone, JM 2017, Neutrosophic segmentation of breast lesions for dedicated breast CT. in Medical Imaging 2017: Computer-Aided Diagnosis. vol. 10134, 101340Q, SPIE, Medical Imaging 2017: Computer-Aided Diagnosis, Orlando, United States, 2/13/17. https://doi.org/10.1117/12.2254128
Lee J, Nishikawa RM, Reiser I, Boone JM. Neutrosophic segmentation of breast lesions for dedicated breast CT. In Medical Imaging 2017: Computer-Aided Diagnosis. Vol. 10134. SPIE. 2017. 101340Q https://doi.org/10.1117/12.2254128
Lee, Juhun ; Nishikawa, Robert M. ; Reiser, Ingrid ; Boone, John M. / Neutrosophic segmentation of breast lesions for dedicated breast CT. Medical Imaging 2017: Computer-Aided Diagnosis. Vol. 10134 SPIE, 2017.
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