Abstract book (pdf) - ICPR 2010

ments. The method proposed improves upon wave intensity wall analysis, WIWA, and opens up a possibility for easy and
efficient analysis and diagnosis of vascular disease through noninvasive ultrasonic examination.
09:00-11:10, Paper WeAT9.29
Quantification of Subcellular Molecules in Tissue MicroArray
Can, Ali, General Electric
Gerdes, Michael, General Electric
Bello, Musodiq, General Electric
Quantifying expression levels of proteins with sub cellular resolution is critical to many applications ranging from biomarker
discovery to treatment planning. In this paper, we present a fully automated method and a new metric that quantifies
the expression of target proteins in immunohisto-chemically stained tissue microarray (TMA) samples. The proposed
metric is superior to existing intensity or ratio-based methods. We compared performance with the majority decision of a
group of 19 observers scoring estrogen receptor (ER) status, achieving a detection rate of 96% with 90% specificity. The
presented methods will accelerate the processes of biomarker discovery and transitioning of biomarkers from research
bench to clinical utility.
09:00-11:10, Paper WeAT9.30
Actual Midline Estimation from Brain CT Scan using Multiple Regions Shape Matching
Chen, Wenan, Virginia Commonwealth Univ.
Ward, Kevin, Virginia Commonwealth Univ.
Kayvan, Najarian, Virginia Commonwealth Univ.
Computer assisted medical image processing can extract vital information that may be elusive to human eyes. In this paper,
an algorithm is proposed to automatically estimate the position of the actual midline from the brain CT scans using multiple
regions shape matching. The method matches feature points identified from a set of ventricle templates, extracted from
MRI, with the corresponding feature points in the segmented ventricles from CT images. Then based on the matched
feature points, the position of the actual midline is estimated. The proposed multiple regions shape matching algorithm
addresses the deformation problem arising from the intrinsic multiple regions nature of the brain ventricles. Experiments
on the CT scans from patients with traumatic brain injuries (TBI) show promising results, particularly the proposed algorithm
proves to be quite robust.
09:00-11:10, Paper WeAT9.31
Boosting Alzheimer Disease Diagnosis using PET Images
Silveira, Margarida, Inst. Superior Técnico / Inst. de Sistema e Robótica
Marques, Jorge S., Inst. Superior Técnico
Alzheimer’s disease (AD) is one of the most frequent type of dementia. Currently there is no cure for AD and early diagnosis
is crucial to the development of treatments that can delay the disease progression. Brain imaging can be a biomarker
for Alzheimer’s disease. This has been shown in several works with MR Images, but in the case of functional imaging
such as PET, further investigation is still needed to determine their ability to diagnose AD, especially at the early stage of
Mild Cognitive Impairment (MCI). In this paper we study the use of PET images of the ADNI database for the diagnosis
of AD and MCI. We adopt a Boosting classification method, a technique based on a mixture of simple classifiers, which
performs feature selection concurrently with the segmentation thus is well suited to high dimensional problems. The Boosting
classifier achieved an accuracy of 90.97% in the detection of AD and 79.63% in the detection of MCI.
09:00-11:10, Paper WeAT9.32
Efficient Quantitative Information Extraction from PCR-RFLP Gel Electrophoresis Images
Maramis, Christos, Aristotle Univ. of Thessaloniki
Delopoulos, Anastasios, Aristotle Univ. of Thessaloniki
For the purpose of PCR-RFLP analysis, as in the case of human papillomavirus (HPV) typing, quantitative information
needs to be extracted from images resulting from one-dimensional gel electrophoresis by associating the image intensity
with the concentration of biological material at the corresponding position on a gel matrix. However, the background intensity
of the image stands in the way of quantifying this association. We propose a novel, efficient methodology for mod-
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