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Interactive Level Set Segmentation for Image-Guided Therapy

Interactive Level Set Segmentation for Image-Guided Therapy,10.1109/ISBI.2009.5193243,Nir Ben-Zadok,Tammy Riklin-Raviv,Nahum Kiryati

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Interactive Level Set Segmentation for Image-Guided Therapy   (Citations: 4)
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Image-guided therapy procedures require the patient to remain still throughout the image acquisition, data analysis and therapy. This imposes a tight time constraint on the over-all process. Automatic extraction of the pathological regions prior to the therapy can be faster than the customary manual segmentation performed by the physician. However, the image data alone is usually not sufficient for reliable and unambiguous computerized segmentation. Thus, the oversight of an experienced physician remains mandatory. We present a novel segmentation framework, that allows user feedback. A few mouse-clicks of the user, discrete in nature, are represented as a continuous energy term that is incorporated into a level-set functional. We demonstrate the proposed method on MR scans of uterine fibroids acquired prior to focused ultrasound ablation treatment. The experiments show that with a minimal user input, automatic segmentation results become practically identical to manual expert segmentation.
Conference: IEEE International Symposium on Biomedical Imaging , pp. 1079-1082, 2009
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    • ...However, recent presentations of interactive, level set based segmentation tools by Ben-Zadok et al. [2] and Cremers et al. [8] might indicate a change in that respect...
    • ...Ben-Zadok et al. [2] recently presented a volume segmentation tool based on level sets that focuses on image-guided therapy...
    • ...While Ben-Zadok et al. [2] and Cremers et al. [8] presented promising advances towards interactive level set segmentation, their approaches do not provide probabilistic results...

    Jörg-Stefan Praßni, et al. Uncertainty-Aware Guided Volume Segmentation

    • ...However, the cost function in (4) does not use any user interaction beyond an initialization for f. Recently, there has been work on incorporating user labels in the level set method by explicitly adding a user term in the cost function [5, 6]. User informationis representedby a labelfunction...
    • ...This term is similar to the one used by [5, 6], except that f � uses the generalized distance transform label propagation, as opposed to an isotropic propagation...
    • ...includes other objects, e.g., heart and stomach, while the results using user information as in [5, 6] lose the tip of the liver...

    Yingxuan Zhu, et al. Exploiting user labels with generalized distance transforms random fie...

    • ...In order to obtain a satisfactory result, the segmentation either happens in a specified area, i.e., narrowing down the target region to have as few object(s) as possible, e.g., Fig. 1 in [2]; or uses plenty of training data, such as atlas...
    • ...Moreover, the generated edges from level set method are close, which is good for segmenting medical objects [4, 5]. For example, Cremers et al. and Ben-Zadok et al. applied level set methods in interactive segmentation recently [2, 6]. Their methods level up/down the pixels around the user labeled pixels according to the distance between the user decided pixels and the unknown pixels, which work effectively in solo round shape object, but ...

    Yingxuan Zhu, et al. Interactive segmentation of medical images using belief propagation wi...

    • ...Among the interactive volume segmentation methods (volume segmentation systems), we can find the systems proposed in [5,6,7,8,9,10]...

    Ludovic Paulhac, et al. Interactive Segmentation of 3D Images Using a Region Adjacency Graph R...

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