The use of computer image analyses in the assessment of chosen histoclinical features of nephroblastoma cells in children.
نویسندگان
چکیده
The goal of the research was to assess the nuclear morphometric discriminant function (MV(f)) in the analyzed group of nephroblastomas and to evaluate its potential prognostic value. We found a statistically important correlation between favourable histology of Wilms' tumours (according to SIOP 93-01 and SIOP 2001 classifications of kidney tumours of childhood) and low values of MV(f) discriminant function, which was also associated with the best prognosis for the patients. We believe that MV(f) assessment may be a helpful tool in making prognosis in doubtful cases of nephroblastomas in children.
منابع مشابه
A Novel Method for Content Base Image Retrieval Using Combination of Local and Global Features
Content-based image retrieval (CBIR) has been an active research topic in the last decade. In this paper we proposed an image retrieval method using global and local features. Firstly, for local features extraction, SURF algorithm produces a set of interest points for each image and a set of 64-dimensional descriptors for each interest points and then to use Bag of Visual Words model, a cluster...
متن کاملImage authentication using LBP-based perceptual image hashing
Feature extraction is a main step in all perceptual image hashing schemes in which robust features will led to better results in perceptual robustness. Simplicity, discriminative power, computational efficiency and robustness to illumination changes are counted as distinguished properties of Local Binary Pattern features. In this paper, we investigate the use of local binary patterns for percep...
متن کاملA Deep Model for Super-resolution Enhancement from a Single Image
This study presents a method to reconstruct a high-resolution image using a deep convolution neural network. We propose a deep model, entitled Deep Block Super Resolution (DBSR), by fusing the output features of a deep convolutional network and a shallow convolutional network. In this way, our model benefits from high frequency and low frequency features extracted from deep and shallow networks...
متن کاملA Novel Method for Content Base Image Retrieval Using Combination of Local and Global Features
Content-based image retrieval (CBIR) has been an active research topic in the last decade. In this paper we proposed an image retrieval method using global and local features. Firstly, for local features extraction, SURF algorithm produces a set of interest points for each image and a set of 64-dimensional descriptors for each interest points and then to use Bag of Visual Words model, a cluster...
متن کاملTags Re-ranking Using Multi-level Features in Automatic Image Annotation
Automatic image annotation is a process in which computer systems automatically assign the textual tags related with visual content to a query image. In most cases, inappropriate tags generated by the users as well as the images without any tags among the challenges available in this field have a negative effect on the query's result. In this paper, a new method is presented for automatic image...
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:
- Polish journal of pathology : official journal of the Polish Society of Pathologists
دوره 62 1 شماره
صفحات -
تاریخ انتشار 2011