Abstract: For evaluating the severity of Chronic Obstructive Pulmonary Disease (COPD), one is interested in inspecting the airway wall thickening due to inflammation. Although airway segmentations have being well developed to reconstruct in high order, airway wall segmentation remains a challenge task. While tackling such problem as a multi-surface segmentation, the interrelation within surfaces needs to be considered. We propose a new method for three-dimensional airway wall segmentation using spring structural active contour model. The method incorporates the gravitational field of the image and repelling force field of the inner lumen as the soft constraint and the geometric spring structure of active contour as the hard constraint to approximate a three-dimensional coupled surface readily for thickness measurements. The results show the preservation of topology constraints of coupled surfaces. In conclusion, our springy, soft-tissue-like structure ensures the globally optimal solution and waives the shortness following by the inevitable improper inner surface constraint.
Abstract: COPD is characterized by loss of elastic fibers from
small airways and alveolar walls, with the decrease in elastin
increasing with disease severity. It is unclear why there is a lack of
repair of elastic fibers. We have examined fibroblasts cultured from
lung tissue from normal and COPD subjects to determine if the
secretory profile explains lack of tissue repair. In this study,
fibroblasts were cultured from lung parenchyma of bronchial
carcinoma patients with varying degrees of COPD; controls
(non-COPD, n=5), mild COPD (GOLD 1, n=5) and moderate-severe
COPD (GOLD 2-3, n=12). Measurements were made of proliferation,
senescence-associated beta-galactosidase-1, mRNA expression of
IL-6, IL-8, MMP-1, tropoelastin and versican, and protein levels for
IL-6, IL-8, PGE2, tropoelastin, insoluble elastin, and versican. It was
found that GOLD 2-3 fibroblasts proliferated more slowly (p
Abstract: In this paper, we present user pattern learning
algorithm based MDSS (Medical Decision support system) under
ubiquitous. Most of researches are focus on hardware system, hospital
management and whole concept of ubiquitous environment even
though it is hard to implement. Our objective of this paper is to design
a MDSS framework. It helps to patient for medical treatment and
prevention of the high risk patient (COPD, heart disease, Diabetes).
This framework consist database, CAD (Computer Aided diagnosis
support system) and CAP (computer aided user vital sign prediction
system). It can be applied to develop user pattern learning algorithm
based MDSS for homecare and silver town service. Especially this
CAD has wise decision making competency. It compares current vital
sign with user-s normal condition pattern data. In addition, the CAP
computes user vital sign prediction using past data of the patient. The
novel approach is using neural network method, wireless vital sign
acquisition devices and personal computer DB system. An intelligent
agent based MDSS will help elder people and high risk patients to
prevent sudden death and disease, the physician to get the online
access to patients- data, the plan of medication service priority (e.g.
emergency case).