Abstract
The determination of tumor margins during surgical resection remains a challenging task. A complete removal of malignant tissue and conservation of healthy tissue is important for the preservation of organ function, patient satisfaction, and quality of life. Visual inspection and palpation is not sufficient for discriminating between malignant and normal tissue types. Hyperspectral imaging (HSI) technology has the potential to noninvasively delineate surgical tumor margin and can be used as an intra-operative visual aid tool. Since histological images provide the ground truth of cancer margins, it is necessary to warp the cancer regions in ex vivo histological images back to in vivo hyperspectral images in order to validate the tumor margins detected by HSI and to optimize the imaging parameters. In this paper, principal component analysis (PCA) is utilized to extract the principle component bands of the HSI images, which is then used to register HSI images with the corresponding histological image. Affine registration is chosen to model the global transformation. A B-spline free form deformation (FFD) method is used to model the local non-rigid deformation. Registration experiment was performed on animal hyperspectral and histological images. Experimental results from animals demonstrated the feasibility of the hyperspectral imaging method for cancer margin detection.
| Original language | English (US) |
|---|---|
| Title of host publication | Medical Imaging 2014 |
| Subtitle of host publication | Image-Guided Procedures, Robotic Interventions, and Modeling |
| Publisher | SPIE |
| ISBN (Print) | 9780819498298 |
| DOIs | |
| State | Published - Jan 1 2014 |
| Externally published | Yes |
| Event | Medical Imaging 2014: Image-Guided Procedures, Robotic Interventions, and Modeling - San Diego, CA, United States Duration: Feb 18 2014 → Feb 20 2014 |
Publication series
| Name | Progress in Biomedical Optics and Imaging - Proceedings of SPIE |
|---|---|
| Volume | 9036 |
| ISSN (Print) | 1605-7422 |
Other
| Other | Medical Imaging 2014: Image-Guided Procedures, Robotic Interventions, and Modeling |
|---|---|
| Country | United States |
| City | San Diego, CA |
| Period | 2/18/14 → 2/20/14 |
Fingerprint
Keywords
- affine registration
- Bspline free form deformation
- head and neck cancer
- Medical hyperspectral imaging
- surgical margin delineation
ASJC Scopus subject areas
- Electronic, Optical and Magnetic Materials
- Biomaterials
- Atomic and Molecular Physics, and Optics
- Radiology Nuclear Medicine and imaging
Cite this
Hyperspectral imaging for cancer surgical margin delineation : Registration of hyperspectral and histological images. / Lu, Guolan; Halig, Luma; Wang, Dongsheng; Chen, Zhuo Georgia; Fei, Baowei.
Medical Imaging 2014: Image-Guided Procedures, Robotic Interventions, and Modeling. SPIE, 2014. 90360S (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 9036).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Hyperspectral imaging for cancer surgical margin delineation
T2 - Registration of hyperspectral and histological images
AU - Lu, Guolan
AU - Halig, Luma
AU - Wang, Dongsheng
AU - Chen, Zhuo Georgia
AU - Fei, Baowei
PY - 2014/1/1
Y1 - 2014/1/1
N2 - The determination of tumor margins during surgical resection remains a challenging task. A complete removal of malignant tissue and conservation of healthy tissue is important for the preservation of organ function, patient satisfaction, and quality of life. Visual inspection and palpation is not sufficient for discriminating between malignant and normal tissue types. Hyperspectral imaging (HSI) technology has the potential to noninvasively delineate surgical tumor margin and can be used as an intra-operative visual aid tool. Since histological images provide the ground truth of cancer margins, it is necessary to warp the cancer regions in ex vivo histological images back to in vivo hyperspectral images in order to validate the tumor margins detected by HSI and to optimize the imaging parameters. In this paper, principal component analysis (PCA) is utilized to extract the principle component bands of the HSI images, which is then used to register HSI images with the corresponding histological image. Affine registration is chosen to model the global transformation. A B-spline free form deformation (FFD) method is used to model the local non-rigid deformation. Registration experiment was performed on animal hyperspectral and histological images. Experimental results from animals demonstrated the feasibility of the hyperspectral imaging method for cancer margin detection.
AB - The determination of tumor margins during surgical resection remains a challenging task. A complete removal of malignant tissue and conservation of healthy tissue is important for the preservation of organ function, patient satisfaction, and quality of life. Visual inspection and palpation is not sufficient for discriminating between malignant and normal tissue types. Hyperspectral imaging (HSI) technology has the potential to noninvasively delineate surgical tumor margin and can be used as an intra-operative visual aid tool. Since histological images provide the ground truth of cancer margins, it is necessary to warp the cancer regions in ex vivo histological images back to in vivo hyperspectral images in order to validate the tumor margins detected by HSI and to optimize the imaging parameters. In this paper, principal component analysis (PCA) is utilized to extract the principle component bands of the HSI images, which is then used to register HSI images with the corresponding histological image. Affine registration is chosen to model the global transformation. A B-spline free form deformation (FFD) method is used to model the local non-rigid deformation. Registration experiment was performed on animal hyperspectral and histological images. Experimental results from animals demonstrated the feasibility of the hyperspectral imaging method for cancer margin detection.
KW - affine registration
KW - Bspline free form deformation
KW - head and neck cancer
KW - Medical hyperspectral imaging
KW - surgical margin delineation
UR - http://www.scopus.com/inward/record.url?scp=84902108092&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84902108092&partnerID=8YFLogxK
U2 - 10.1117/12.2043805
DO - 10.1117/12.2043805
M3 - Conference contribution
C2 - 25328640
AN - SCOPUS:84902108092
SN - 9780819498298
T3 - Progress in Biomedical Optics and Imaging - Proceedings of SPIE
BT - Medical Imaging 2014
PB - SPIE
ER -