Assessment of automatic segmentation of teeth using a watershed-based method

Galibourg, Antoine; Dumoncel, Jean; Telmon, Norbert; Calvet, Adèle; Michetti, Jérôme; Maret, Delphine

doi:10.1259/dmfr.20170220

Cited by 30 publications

(23 citation statements)

References 35 publications

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“…Number of image objects produced by the two segmentation methods was close to eaach other, this is observed that segmentation quality increased significantly [6]. However, result of [5] and [6] still carry oversegmentation due to difficulties to obtained correct edges from it is object. The complexity to retrieve edges from natural image object is high and indeed become an open research issue [7].…”

Section: Introductionsupporting

confidence: 52%

“…Galibourg et al compared the effect of automatic segmentation using a Watershed-based method with semi-automatic segmentation on 52 teeth micro computed tomograph image for accuracy and reproducibility of 3D reconstruction. From experiment result show that automatic segmentation have similar tooth volumes when compared with semi-automatic segmentation, the difference value found at the cervical margins and incisal edges but general form was preserved [5]. Kavzoglu and Tonbul compared region-based and edge-based segmentation methods using Area fit index (AFI) and Quality rate (Qr) metrics to assessed segmentation quality metrics of satellite images.…”

Section: Introductionmentioning

confidence: 99%

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Algorithm for Identifying Objects in The Relief Image Using Watershed Segmentation

Auliasari¹,

Orisa²

2017

SJI

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This study aims to automate the process of understanding temple relief, despite the difficulties to analyze the contents of natural images. Three preprocessing stages are develop in this research namely edge detection based on convolution (EC), edge detection based on gaussian (EG) and Hybrid which is a combination between edge detection based on convolution and gaussian. These algorithm is to support the operation of Watershed transform to segment relief images. A set of relief images obtained from several temples near Malang City are used in this experiment. Two experimental parameter are develop in order to measure the performance of these algorithm, namely number of object and quality of retrieval from segmentation result. The result of experiment show that hybrid approach deliver the best performances compare the other approaches.

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Section: Introductionsupporting

confidence: 52%

Section: Introductionmentioning

confidence: 99%

Algorithm for Identifying Objects in The Relief Image Using Watershed Segmentation

Auliasari¹,

Orisa²

2017

SJI

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“…20 Use of watershed methods to segment teeth has been described. [21][22][23][24] Naumovich et al suggested that the watershed method could be extended to segment 'the jaws' from CBCT, but did not report images of such segmentation. 24 Each of these methods of dental segmentation requires manual placement of markers in each case.…”

mentioning

confidence: 99%

Marker-based watershed transform method for fully automatic mandibular segmentation from CBCT images

Fan

Beare

Matthews

et al. 2019

Dentomaxillofacial Radiology

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Objectives: To propose a reliable and practical method for automatically segmenting the mandible from CBCT images. Methods: The marker-based watershed transform is a region-growing approach that dilates or "floods" predefined markers onto a height map whose ridges denote object boundaries. We applied this method to segment the mandible from the rest of the CBCT image. The height map was generated to enhance the sharp decreases of intensity at the mandible/tissue border and suppress noise by computing the intensity gradient image of the CBCT itself. Two sets of markers, "mandible" and "background" were automatically placed inside and outside the mandible, respectively in a novel image using image registration. The watershed transform flooded the gradient image by dilating the markers simultaneously until colliding at watershed lines, estimating the mandible boundary. CBCT images of 20 adolescent subjects were chosen as test cases. Segmentation accuracy of the proposed method was evaluated by measuring overlap (Dice similarity coefficient) and boundary agreement against a well-accepted interactive segmentation method described in the literature. Results: The Dice similarity coefficient was 0.97 ± 0.01 (mean ± SD), indicating almost complete overlap between the automatically and the interactively segmented mandibles. Boundary deviations were predominantly under 1 mm for most of the mandibular surfaces. The errors were mostly from bones around partially erupted wisdom teeth, the condyles and the dental enamels, which had minimal impact on the overall morphology of the mandible. conclusions: The marker-based watershed transform method produces segmentation accuracy comparable to the well-accepted interactive segmentation approach.

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“…In this software, the tool is called "Watershed, " which is within the option of segmentation editor. The process to follow is detailed and explained in Galibourg et al (2017).…”

Section: Removing Endocast Materialsmentioning

confidence: 99%

Toward an “Ancient” Virtual World: Improvement Methods on X-ray CT Data Processing and Virtual Reconstruction of Fossil Skulls

Pérez‐Ramos

Figueirido

2020

Front. Earth Sci.

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This article focuses on new virtual advances to solve technical problems usually encountered by paleontologists when using X-ray computed tomography (XCT), such as (i) the limited scanning envelope (i.e., field of view of CT systems/machines) to acquire data on large structures; (ii) the use in the same study of biological objects acquired with different types of computed tomography systems (medical and laboratory XCTs and laboratory high-resolution XµCT) and therefore different resolutions; and (iii) matrix removal within the fossil (e.g., cranial cavities, intratrabecular cavities, among other cavities). All these problems are very common in paleontology, and therefore, solving them is important to save effort and the time invested in data processing. In this article, we propose various solutions to tackle these issues, based on new technical advances focused on improving and processing the images obtained from XCT. Other aspects include image filtering and histogram calibration to remove background noise and artifacts. Such artifacts can result from dense mineral inclusion occurring during the fossilization process or derived from anthropogenic restoration of the sample. Accordingly, here, we provide a protocol to acquire data on samples with size that exceed the scanning envelope of the X-ray tomography machine, joining the parts with enough accuracy, and we propose the use of the interpolation "bicubic" method. Moreover, using this method, it is possible to use medical/laboratory XCT data together with XµCT data and therefore opening new ways to manipulate the acquired data within the image stack. Another advantage is the use of plugins for quantitative analysis, which require data with isometric voxels, such as the plugin BoneJ of the software ImageJ. We also deal with the problem of removing the exogenous material that usually fills the internal cavities of fossils by means of using filters based on edge detection by gradient. Applying this method, it is possible to segment the non-bony matrix parts more quickly and efficiently. All of this is exemplified using five fossil skulls belonging to the cave bear group (Ursus spelaeus sensu lato), an iconic fossil species from the Pleistocene of Eurasia.

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Assessment of automatic segmentation of teeth using a watershed-based method

Cited by 30 publications

References 35 publications

Algorithm for Identifying Objects in The Relief Image Using Watershed Segmentation

Algorithm for Identifying Objects in The Relief Image Using Watershed Segmentation

Marker-based watershed transform method for fully automatic mandibular segmentation from CBCT images

Toward an “Ancient” Virtual World: Improvement Methods on X-ray CT Data Processing and Virtual Reconstruction of Fossil Skulls

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