Panrasee Ritthipravat

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This paper describes a framework for automatic nasopharyngeal carcinoma segmentation from CT images. The proposed technique is based on the Region Growing Method. It is automatic segmentation in which an initial seed is generated without human intervention. The seed is generated from a probabilistic map representing the chances of it being tumor. This map(More)
In this paper, dynamic path planning of two mobile robots using a modified Hopfield neural network is studied. An area which excludes obstacles and allows gradually changing of activation level of neurons is derived in each step. Next moving step can be determined by searching the next highest activated neuron. By learning repeatedly, the steps will be(More)
This paper aims to review the use of artificial neural networks (ANNs) in prediction of cancer recurrence. The sources of publications were randomly selected from PUBMED database, IEEE explore, and the google search engine with the keywords for searching as “recurrence” or “relapse” or “disease free” +(More)
PURPOSE This paper proposes a new image segmentation technique for identifying nasopharyngeal tumor regions in CT images. The technique is modified from the seeded region growing (SRG) approach that is simple but sensitive to image intensity of the initial seed. METHODS CT images of patients with nasopharyngeal carcinoma (NPC) were collected from(More)
This paper presents an automatic segmentation technique for identifying nasopharyngeal carcinoma regions in CT images. The proposed technique is based on the region growing method by which an initial seed is automatically generated. A probabilistic map representing a chance of being the tumor pixel in each CT image will be created and used for initial seed(More)
In this paper, path planning of a mobile robot by using a modified Hopfield neural network is studied. An area, which excludes obstacles and allows gradually changing of activation level of neurons from a starting point to a goal, is derived. Path can be constructed in this area by searching the next highest activated neuron. Even though asymmetric weight(More)
MRI inter-slice gap is required during the image acquisition process in order to prevent leakage protons which cause blurred images. The gap is one of the major obstacles in image analysis, particularly in various modern computer aided diagnosis applications because the data in those inter-slice gaps disappear. In this paper, an inter-slice interpolation(More)