Segmenting Lung Fields in Serial Chest Radiographs Using Both Population and Patient-Specific Shape Statistics
نویسندگان
چکیده
This paper presents a new deformable model using both population-based and patient-specific shape statistics to segment lung fields from serial chest radiographs. First, a modified scale-invariant feature transform (SIFT) local descriptor is used to characterize the image features in the vicinity of each pixel, so that the deformable model deforms in a way that seeks for the region with similar SIFT local descriptors; second, the deformable model is constrained by both population-based and patient-specific shape statistics. At first, population-based shape statistics plays an leading role when the number of serial images is small, and gradually, patient-specific shape statistics plays a more and more important role after a sufficient number of segmentation results on the same patient have been obtained. The proposed deformable model can adapt to the shape variability of different patients, and obtain more robust and accurate segmentation results.
منابع مشابه
Learning Longitudinal Deformations for Adaptive Segmentation of Lung Fields from Serial Chest Radiographs
We previously developed a deformable model for segmenting lung fields in serial chest radiographs by using both population-based and patientspecific shape statistics, and obtained higher accuracy compared to other methods. However, this method uses an ad hoc way to evenly partition the boundary of lung fields into some short segments, in order to capture the patient-specific shape statistics fr...
متن کاملSegmentation of anatomical structures in chest radiographs using supervised methods: a comparative study on a public database Revised version
The task of segmenting the lung fields, the heart, and the clavicles in standard posterior-anterior chest radiographs is considered. Three supervised segmentation methods are compared: active shape models, active appearance models, both first proposed by Cootes et al. [1] and a multi-resolution pixel classification method that employs a multi-scale filter bank of Gaussian derivatives and a k-ne...
متن کاملShielding Active Shape Models against Weak Lung Field Boundaries for Segmentation of Chest Radiographs
A novel active shape model (ASM) segmentation scheme is proposed, for the detection of the lung field boundaries in chest radiographs. The proposed scheme is robust in the presence of weak lung field boundaries, which are recognized as a common cause of missegmentation. This situation is prevalent in chest radiographs obtained from patients with abnormalities, such as lung consolidations, or ev...
متن کاملPre-Classification of Chest Radiographs for Improved Active Shape Model Segmentation of Ribs
The parenchymal and skeletal structure as recorded on chest radiographs can vary significantly from person to person. The person’s height, width, age, gender, and other factors will result in significant variations in the presentation of these structures. As a result, the application of an active shape model (ASM) for segmentation can be problematic. The segmentation task can be made easier if,...
متن کاملChest X-ray screening improves outcome in lung cancer. A reappraisal of randomized trials on lung cancer screening.
It is believed that population-based screening for cancer should be advocated only when screening reduces disease-specific mortality. Four randomized controlled studies on lung cancer screening have been conducted in male cigarette smokers, and none has demonstrated reduced mortality. Accordingly, no organization that formulates screening policy advocates any specific early detection strategies...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
دوره 9 Pt 1 شماره
صفحات -
تاریخ انتشار 2006