@article {1004,
	title = {Brain atrophy in relapsing-remitting multiple sclerosis: Fractional volumetric analysis of gray matter and white matter},
	journal = {RADIOLOGY},
	volume = {220},
	year = {2001},
	note = {UT: 000170616700008ScopusID: 0034866802doi: 10.1148/radiol.2203001776},
	month = {2001///},
	pages = {606 - 610},
	abstract = {PURPOSE: To determine the fractional brain tissue volume changesin the gray matter and white matter of patients with relapsing-
remitting multiple sclerosis (MS) and to correlate these 
measurements with clinical disability and total lesion load. 
MATERIALS AND METHODS: Thirty patients with relapsing-remitting 
MS and 25 healthy control subjects underwent magnetic resonance 
imaging. Fractional brain tissue volumes (tissue volume relative 
to total intracranial volume) were obtained from the total 
segmented gray matter and white matter in each group and were 
analyzed. RESULTS: The fractional volume of white matter versus 
that of gray matter was significantly lower (-6.4\%) in patients 
with MS (P <.0001) than in control subjects. Neither gray matter 
nor white matter fractional volume measurements correlated with 
clinical disability in the patients with MS. CONCLUSION: Loss of 
brain parenchymal volume in patients with relapsing-remitting MS 
is predominantly confined to white matter. Analysis of 
fractional brain tissue volumes provides additional information 
useful in characterizing MS and may have potential in evaluating 
treatment strategies.
},
	isbn = {0033-8419},
	author = {Yiyue Ge and Robert J Grossman and Jayaram K Udupa and James S Babb and L{\'a}szl{\'o} G{\'a}bor Ny{\'u}l and Dennis L Kolson}
}
@article {1002,
	title = {Multiprotocol MR image segmentation in multiple sclerosis: Experience with over 1,000 studies},
	journal = {ACADEMIC RADIOLOGY},
	volume = {8},
	year = {2001},
	note = {UT: 000171987900006ScopusID: 0034767131doi: 10.1016/S1076-6332(03)80723-7},
	month = {2001///},
	pages = {1116 - 1126},
	abstract = {RATIONALE AND OBJECTIVES: Multiple sclerosis (MS) is an acquireddisease of the central nervous system. Several clinical measures 
are commonly used to express the severity of the disease, 
including the Expanded Disability Status Scale and the 
ambulation index. These measures are subjective and may be 
difficult to reproduce. The aim of this research is to 
investigate the possibility of developing more objective 
measures derived from MR imaging. MATERIALS AND METHODS: Various 
magnetic resonance (MR) imaging protocols are being investigated 
for the study of MS. Seeking to replace the Expanded Disability 
Status Scale and ambulation index with an objective means to 
assess the natural course of the disease and its response to 
therapy, the authors have developed multiprotocol MR image 
segmentation methods based on fuzzy connectedness to quantify 
both macrosopic features of the disease (lesions, gray matter, 
white matter, cerebrospinal fluid, and brain parenchyma) and the 
microscopic appearance of diseased white matter. Over 1,000 
studies have been processed to date. RESULTS: By far the 
strongest correlations with the clinical measures were 
demonstrated by the magnetization transfer ratio histogram 
parameters obtained for the various segmented tissue regions. 
These findings emphasize the importance of considering the 
microscopic and diffuse nature of the disease in the individual 
tissue regions. Brain parenchymal volume also demonstrated a 
strong correlation with clinical measures, which suggests that 
brain atrophy is an important disease indicator. CONCLUSION: 
Fuzzy connectedness is a viable, highly reproducible 
segmentation method for studying MS.
},
	isbn = {1076-6332},
	author = {Jayaram K Udupa and L{\'a}szl{\'o} G{\'a}bor Ny{\'u}l and Yiyue Ge and Robert J Grossman}
}
@booklet {1076,
	title = {Brain Atrophy in Relapsing-Remitting Multiple Sclerosis: A Fractional Volumetric Analysis of Gray Matter and White Matter},
	year = {2000},
	month = {2000///},
	author = {Yiyue Ge and Robert J Grossman and Jayaram K Udupa and James S Babb and L{\'a}szl{\'o} G{\'a}bor Ny{\'u}l and Dennis L Kolson}
}
@booklet {1074,
	title = {Magnetization Transfer Ratio Histogram Analysis of Normal Appearing Gray Matter and White Matter in MS},
	year = {2000},
	month = {2000///},
	author = {Yiyue Ge and Robert J Grossman and Jayaram K Udupa and James S Babb and L{\'a}szl{\'o} G{\'a}bor Ny{\'u}l and Dennis L Kolson and Lois J Mannon and Joseph C McGowan}
}
@article {994,
	title = {Multiple sclerosis: Magnetization transfer histogram analysis of segmented normal-appearing white matter},
	journal = {RADIOLOGY},
	volume = {216},
	year = {2000},
	note = {UT: 000088430800008ScopusID: 0033894599},
	month = {2000///},
	pages = {351 - 355},
	abstract = {PURPOSE: To investigate and characterize the global distributionof magnetization transfer (MT) ratio values of normal-appearing 
white matter (NAWM) in patients with relapsing-remitting 
multiple sclerosis (MS) and test the hypothesis that the MT 
histogram for NAWM reflects disease progression. MATERIALS AND 
METHODS: Conventional and MT magnetic resonance (MR) images were 
obtained in 23 patients and 25 healthy volunteers. Clinical 
tests for comparison with the MT histogram parameters included 
the Extended Disability Status Scale and the ambulation index. 
Lesion load calculated with T2-weighted MR images and whole-
brain and white matter volumes were measured. RESULTS: The 
location of the MT histogram peak and the mean MT ratio for NAWM 
were significantly lower in patients with MS than in control 
subjects. In longitudinal studies, the histogram peak location 
and mean MT ratio shifted in the direction of normal values as 
the duration of disease increased. A mean of 26.5\% of the volume 
of new lesions identified on the later studies were demonstrated 
to have originated in NAWM corresponding to "lost" pixels on the 
histogram. CONCLUSION: MT histogram analysis of NAWM, including 
longitudinal analysis, may provide new prognostic information 
regarding lesion formation and increase understanding of the 
course of the disease.
},
	isbn = {0033-8419},
	author = {Isabelle Catalaa and Robert J Grossman and Dennis L Kolson and Jayaram K Udupa and L{\'a}szl{\'o} G{\'a}bor Ny{\'u}l and Lougang Wei and Xuan Zhang and Marcia Polansky and Lois J Mannon and Joseph C McGowan}
}
@inbook {1013,
	title = {Multiprotocol MR image segmentation in multiple sclerosis: experience with over 1000 studies},
	booktitle = {Medical Imaging 2000: Image Processing},
	year = {2000},
	note = {ScopusID: 0033721228doi: 10.1117/12.387606},
	month = {2000///},
	pages = {1017 - 1027},
	publisher = {SPIE},
	organization = {SPIE},
	address = {Bellingham; Washington},
	abstract = {Multiple Sclerosis (MS) is an acquired disease of the centralnervous system. Subjective cognitive and ambulatory test scores 
on a scale called EDSS are currently utilized to assess the 
disease severity. Various MRI protocols are being investigated 
to study the disease based on how it manifests itself in the 
images. In an attempt to eventually replace EDSS by an objective 
measure to assess the natural course of the disease and its 
response to therapy, we have developed image segmentation 
methods based on fuzzy connectedness to quantify various objects 
in multiprotocol MRI. These include the macroscopic objects such 
as lesions, the gray matter (GM), white matter (WM), 
cerebrospinal fluid (CSF), and brain parenchyma as well as the 
microscopic aspects of the diseased WM. Over 1000 studies have 
been processed to date. By far the strongest correlations with 
the clinical measures were demonstrated by the Magnetization 
Transfer Ratio (MTR) histogram parameters obtained for the 
various segmented tissue regions emphasizing the importance of 
considering the microscopic/diffused nature of the disease in 
the individual tissue regions. Brain parenchymal volume also 
demonstrated a strong correlation with the clinical measures 
indicating that brain atrophy is an important indicator of the 
disease. Fuzzy connectedness is a viable segmentation method for 
studying MS.
},
	author = {Jayaram K Udupa and L{\'a}szl{\'o} G{\'a}bor Ny{\'u}l and Yiyue Ge and Robert J Grossman},
	editor = {Kenneth M Hanson}
}
@article {1003,
	title = {Numerical tissue characterization in MS via standardization of the MR image intensity scale},
	journal = {JOURNAL OF MAGNETIC RESONANCE IMAGING},
	volume = {12},
	year = {2000},
	note = {UT: 000171295400008ScopusID: 0033754689doi: 10.1002/1522-2586(200011)12:5\&lt;715::AID-JMRI8\&gt;3.0.CO;2-D},
	month = {2000///},
	pages = {715 - 721},
	abstract = {Image intensity standardization is a recently developedpostprocessing method that is capable of correcting the signal 
intensity variations in MR images. We evaluated signal intensity 
of healthy and diseased tissues in 10 multiple sclerosis (MS) 
patients based on standardized dual fast spin-echo MR images 
using a numerical postprocessing technique. The main idea of 
this technique is to deform the volume image histogram of each 
study to match a standard histogram and to utilize the resulting 
transformation to map the image intensities into standard scale. 
Upon standardization, the coefficients of variation of signal 
intensities for each segmented tissue (gray matter, white 
matter, lesion plaques, and diffuse abnormal white matter) in 
all patients were significantly smaller (2.3-9.2 times) than in 
the original images, and the same tissues from different 
patients looked alike, with similar intensity characteristics. 
Numerical tissue characterizability of different tissues in MS 
achieved by standardization offers a fixed tissue-specific 
meaning for the numerical values and can significantly 
facilitate image segmentation and analysis.
},
	isbn = {1053-1807},
	author = {Yiyue Ge and Jayaram K Udupa and L{\'a}szl{\'o} G{\'a}bor Ny{\'u}l and Lougang Wei and Robert J Grossman}
}
@conference {1019,
	title = {Numerical Tissue Characterization in MS via Standardization of the MR Image Intensity Scale},
	booktitle = {International Society for Magnetic Resonance in Medicine: Eight Scientific Meeting and Exhibition},
	year = {2000},
	month = {Apr 2000},
	pages = {579},
	address = {Berkeley},
	author = {Yiyue Ge and Jayaram K Udupa and L{\'a}szl{\'o} G{\'a}bor Ny{\'u}l and Lougang Wei and Robert J Grossman}
}
@conference {1018,
	title = {Tissue Characterization in Relapsing-remitting and Secondary-progressive MS via Magnetization Transfer Ratio},
	booktitle = {International Society for Magnetic Resonance in Medicine: Eight Scientific Meeting and Exhibition},
	year = {2000},
	month = {Apr 2000},
	pages = {1189},
	address = {Berkeley},
	author = {Yiyue Ge and Robert J Grossman and Jayaram K Udupa and James S Babb and L{\'a}szl{\'o} G{\'a}bor Ny{\'u}l and Joseph C McGowan}
}
@booklet {1072,
	title = {Magnetization Transfer Histogram Analysis of Segmented Normal- Appearing White Matter in Multiple Sclerosis},
	year = {1999},
	month = {1999///},
	author = {Isabelle Catalaa and Robert J Grossman and Jayaram K Udupa and L{\'a}szl{\'o} G{\'a}bor Ny{\'u}l and Dennis L Kolson and Lougang Wei and Xuan Zhang and Marcia Polansky and Lois J Mannon and Joseph C McGowan}
}
@conference {1020,
	title = {Magnetization Transfer Histogram Analysis of Segmented Normal-Appearing White Matter in Multiple Sclerosis},
	booktitle = {International Society for Magnetic Resonance in Medicine: Seventh Scientific Meeting and Exhibition},
	year = {1999},
	month = {May 1999},
	pages = {957},
	address = {Berkeley},
	author = {Isabelle Catalaa and Robert J Grossman and Dennis L Kolson and L{\'a}szl{\'o} G{\'a}bor Ny{\'u}l and Lougang Wei and Jayaram K Udupa and Marcia Polansky and Joseph C McGowan},
	editor = {*[International Society fo *Medicine]}
}
@booklet {1073,
	title = {Numerical Tissue Characterization in MS via Standardization of the MR Image Intensity Scale},
	year = {1999},
	month = {1999///},
	author = {Yiyue Ge and Jayaram K Udupa and L{\'a}szl{\'o} G{\'a}bor Ny{\'u}l and Lougang Wei and Robert J Grossman}
}
