A deep model based on SegAN, a generative adversarial network (GAN) for medical image segmentation, is proposed for PET-CT image segmentation, utilizing the Mumford-Shah (MS) loss functional. An improved V-net is used for the generator network, while the discriminator network has a similar ...
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Disclosed is an image segmentation method including receiving an image to be segmented and segmenting the received image by using a neural network learned through a Mumford-Shah function-based loss function.JONGCHUL YEBOAH KIM
However, TV minimization often leads to some loss of the image edge information during reducing the image noise and artifacts. To overcome the drawback of TV regularization, this paper proposes to introduce a novel Mumford-Shah total variation (MSTV) regularization by integrating TV minimization and...
The piecewise constant Mumford-Shah (PCMS) model and the Rudin-Osher-Fatemi (ROF) model are two important variational models in image segmentation and image restoration, respectively. In this paper, we explore a linkage between these models. We prove that for the two-phase segmentation problem a...
However, TV minimization often leads to some loss of the image edge information during reducing the image noise and artifacts. To overcome the drawback of TV regularization, this paper proposes to introduce a novel Mumford-Shah total variation (MSTV) regularization by integrating TV minimization and...
The Mumford-Shah model using level set method is more robust than other curve evolution models to detect discontinuities under noisy environment, which has been widely used in the field of medical image segmentation. Consequently, serial computed tomography (CT) image segmentation algorithm based on ...
The region of interests are extracted by using 螕-approximation to a piecewise constant Mumford-Shah functional. However, this method only is not able to accommodate all types of imaging difficulties including noise, artifacts, and loss of information. Therefore, the prior knowledge is necessary to...