Plexiform neurofibroma tissue classification

L. Weizman; L. Hoch; L. Ben Sira; L. Joskowicz; L. Pratt; S. Constantini; D. Ben Bashat

doi:10.1117/12.877491

Plexiform neurofibroma tissue classification

L. Weizman
, L. Hoch
, L. Ben Sira
, L. Joskowicz
, L. Pratt
, S. Constantini
, D. Ben Bashat

The Rachel and Selim Benin School of Engineering and Computer Science

The Hebrew University of Jerusalem

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Plexiform Neurofibroma (PN) is a major complication of NeuroFibromatosis-1 (NF1), a common genetic disease that involving the nervous system. PNs are peripheral nerve sheath tumors extending along the length of the nerve in various parts of the body. Treatment decision is based on tumor volume assessment using MRI, which is currently time consuming and error prone, with limited semi-automatic segmentation support. We present in this paper a new method for the segmentation and tumor mass quantification of PN from STIR MRI scans. The method starts with a user-based delineation of the tumor area in a single slice and automatically detects the PN lesions in the entire image based on the tumor connectivity. Experimental results on seven datasets yield a mean volume overlap difference of 25% as compared to manual segmentation by expert radiologist with a mean computation and interaction time of 12 minutes vs. over an hour for manual annotation. Since the user interaction in the segmentation process is minimal, our method has the potential to successfully become part of the clinical workflow.

Original language	English
Title of host publication	Medical Imaging 2011
Subtitle of host publication	Image Processing
DOIs	https://doi.org/10.1117/12.877491
State	Published - 2011
Event	Medical Imaging 2011: Image Processing - Lake Buena Vista, FL, United States Duration: 14 Feb 2011 → 16 Feb 2011

Publication series

Name	Progress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume	7962

Conference

Conference	Medical Imaging 2011: Image Processing
Country/Territory	United States
City	Lake Buena Vista, FL
Period	14/02/11 → 16/02/11

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Neurofibromatosis-1
Plexiform Neurofibromas
segmentation

ASJC Scopus subject areas

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

Access to Document

10.1117/12.877491

Cite this

@inproceedings{7bade8bb488a47438d45c85346f6560b,

title = "Plexiform neurofibroma tissue classification",

abstract = "Plexiform Neurofibroma (PN) is a major complication of NeuroFibromatosis-1 (NF1), a common genetic disease that involving the nervous system. PNs are peripheral nerve sheath tumors extending along the length of the nerve in various parts of the body. Treatment decision is based on tumor volume assessment using MRI, which is currently time consuming and error prone, with limited semi-automatic segmentation support. We present in this paper a new method for the segmentation and tumor mass quantification of PN from STIR MRI scans. The method starts with a user-based delineation of the tumor area in a single slice and automatically detects the PN lesions in the entire image based on the tumor connectivity. Experimental results on seven datasets yield a mean volume overlap difference of 25\% as compared to manual segmentation by expert radiologist with a mean computation and interaction time of 12 minutes vs. over an hour for manual annotation. Since the user interaction in the segmentation process is minimal, our method has the potential to successfully become part of the clinical workflow.",

keywords = "Neurofibromatosis-1, Plexiform Neurofibromas, segmentation",

author = "L. Weizman and L. Hoch and \{Ben Sira\}, L. and L. Joskowicz and L. Pratt and S. Constantini and \{Ben Bashat\}, D.",

year = "2011",

doi = "10.1117/12.877491",

language = "English",

isbn = "9780819485045",

series = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",

booktitle = "Medical Imaging 2011",

note = "Medical Imaging 2011: Image Processing ; Conference date: 14-02-2011 Through 16-02-2011",

}

Weizman, L, Hoch, L, Ben Sira, L, Joskowicz, L, Pratt, L, Constantini, S & Ben Bashat, D 2011, Plexiform neurofibroma tissue classification. in Medical Imaging 2011: Image Processing., 79623K, Progress in Biomedical Optics and Imaging - Proceedings of SPIE, vol. 7962, Medical Imaging 2011: Image Processing, Lake Buena Vista, FL, United States, 14/02/11. https://doi.org/10.1117/12.877491

TY - GEN

T1 - Plexiform neurofibroma tissue classification

AU - Weizman, L.

AU - Hoch, L.

AU - Ben Sira, L.

AU - Joskowicz, L.

AU - Pratt, L.

AU - Constantini, S.

AU - Ben Bashat, D.

PY - 2011

Y1 - 2011

N2 - Plexiform Neurofibroma (PN) is a major complication of NeuroFibromatosis-1 (NF1), a common genetic disease that involving the nervous system. PNs are peripheral nerve sheath tumors extending along the length of the nerve in various parts of the body. Treatment decision is based on tumor volume assessment using MRI, which is currently time consuming and error prone, with limited semi-automatic segmentation support. We present in this paper a new method for the segmentation and tumor mass quantification of PN from STIR MRI scans. The method starts with a user-based delineation of the tumor area in a single slice and automatically detects the PN lesions in the entire image based on the tumor connectivity. Experimental results on seven datasets yield a mean volume overlap difference of 25% as compared to manual segmentation by expert radiologist with a mean computation and interaction time of 12 minutes vs. over an hour for manual annotation. Since the user interaction in the segmentation process is minimal, our method has the potential to successfully become part of the clinical workflow.

AB - Plexiform Neurofibroma (PN) is a major complication of NeuroFibromatosis-1 (NF1), a common genetic disease that involving the nervous system. PNs are peripheral nerve sheath tumors extending along the length of the nerve in various parts of the body. Treatment decision is based on tumor volume assessment using MRI, which is currently time consuming and error prone, with limited semi-automatic segmentation support. We present in this paper a new method for the segmentation and tumor mass quantification of PN from STIR MRI scans. The method starts with a user-based delineation of the tumor area in a single slice and automatically detects the PN lesions in the entire image based on the tumor connectivity. Experimental results on seven datasets yield a mean volume overlap difference of 25% as compared to manual segmentation by expert radiologist with a mean computation and interaction time of 12 minutes vs. over an hour for manual annotation. Since the user interaction in the segmentation process is minimal, our method has the potential to successfully become part of the clinical workflow.

KW - Neurofibromatosis-1

KW - Plexiform Neurofibromas

KW - segmentation

UR - https://www.scopus.com/pages/publications/79957978256

U2 - 10.1117/12.877491

DO - 10.1117/12.877491

M3 - Conference contribution

SN - 9780819485045

T3 - Progress in Biomedical Optics and Imaging - Proceedings of SPIE

BT - Medical Imaging 2011

T2 - Medical Imaging 2011: Image Processing

Y2 - 14 February 2011 through 16 February 2011

ER -

Plexiform neurofibroma tissue classification

Abstract

Publication series

Conference

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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