TumorGAN: A Multi-Modal Data Augmentation Framework for Brain Tumor Segmentation
نویسندگان
چکیده
منابع مشابه
ilastik for Multi-modal Brain Tumor Segmentation
We present the application of ilastik, the open source interactive learning and segmentation toolkit, for brain tumor segmentation in multi-modal magnetic resonance images. Even without utilizing the interactive nature of the toolkit, we are able to achieve Dice scores comparable to human inter-rater variability and are ranked in the top-5 results for the BraTS 2013 challenge data set, where no...
متن کاملA Generative Model for Brain Tumor Segmentation in Multi-Modal Images
We introduce a generative probabilistic model for segmentation of tumors in multi-dimensional images. The model allows for different tumor boundaries in each channel, reflecting difference in tumor appearance across modalities. We augment a probabilistic atlas of healthy tissue priors with a latent atlas of the lesion and derive the estimation algorithm to extract tumor boundaries and the laten...
متن کاملMulti-Modal Data Augmentation for End-to-end ASR
We present a new end-to-end architecture for automatic speech recognition (ASR) that can be trained using symbolic input in addition to the traditional acoustic input. This architecture utilizes two separate encoders: one for acoustic input and another for symbolic input, both sharing the attention and decoder parameters. We call this architecture a multi-modal data augmentation network (MMDA),...
متن کاملMulti-Atlas based Segmentation of Multi-Modal Brain Images
Brain image analysis is playing a fundamental role in clinical and population-based epidemiological studies. Several brain disorder studies involve quantitative interpretation of brain scans and particularly require accurate measurement and delineation of tissue volumes in the scans. Automatic segmentation methods have been proposed to provide reliability and accuracy of the labelling as well a...
متن کاملA Novel Fuzzy-C Means Image Segmentation Model for MRI Brain Tumor Diagnosis
Accurate segmentation of brain tumor plays a key role in the diagnosis of brain tumor. Preset and precise diagnosis of Magnetic Resonance Imaging (MRI) brain tumor is enormously significant for medical analysis. During the last years many methods have been proposed. In this research, a novel fuzzy approach has been proposed to classify a given MRI brain image as normal or cancer label and the i...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Sensors
سال: 2020
ISSN: 1424-8220
DOI: 10.3390/s20154203