Reliability of using single specialist annotation for designing and evaluating automatic segmentation methods: A skull stripping case study

Laser scanning is considered as one of the most useful and fast technologies for modelling. On the other hand, the size of scan results can vary from hundreds to several million points. As a result, the large volume of the obtained clouds leads to complication at processing the results and increases the time costs. One way to reduce the volume of a point cloud is segmentation, which reduces the amount of data from several million points to a limited number of segments. In this article, we evaluated effect on the performance, the accuracy of various segmentation methods and the geometric accuracy of the obtained models at density changes taking into account the processing time. The results of our experiment were compared with reference data in a form of comparative analysis. As a conclusion, some recommendations for choosing the best segmentation method were proposed.

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The impact of semi-automatic segmentation methods on metabolic tumor volume, intensity and dissemination radiomics in 18F-FDG PET scans of patients with classical Hodgkin lymphoma

Journal of Nuclear Medicine ◽

10.2967/jnumed.121.263067 ◽

2022 ◽

pp. jnumed.121.263067

Author(s):

Julia Driessen ◽

Gerben JC Zwezerijnen ◽

Heiko Schöder ◽

Esther EE Drees ◽

Marie José Kersten ◽

...

Keyword(s):

Hodgkin Lymphoma ◽

Fdg Pet ◽

Tumor Volume ◽

Automatic Segmentation ◽

Metabolic Tumor Volume ◽

Classical Hodgkin Lymphoma ◽

Segmentation Methods ◽

18F Fdg ◽

The Impact ◽

Pet Scans

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Automatic Correction of Gaps in Cerebrovascular Segmentations Extracted from 3D Time-of-Flight MRA Datasets

Methods of Information in Medicine ◽

10.3414/me11-02-0037 ◽

2012 ◽

Vol 51 (05) ◽

pp. 415-422 ◽

Cited By ~ 8

Author(s):

A. Schmidt-Richberg ◽

J. Fiehler ◽

T. Illies ◽

D. Möller ◽

H. Handels ◽

...

Keyword(s):

Level Set ◽

Automatic Segmentation ◽

Time Of Flight ◽

Medical Expert ◽

Consistency Check ◽

Major Drawback ◽

Segmentation Methods ◽

Initial Segmentation ◽

Level Set Approach ◽

Manual Correction

Summary Objectives: Exact cerebrovascular segmentations are required for several applications in today’s clinical routine. A major drawback of typical automatic segmentation methods is the occurrence of gaps within the segmentation. These gaps are typically located at small vessel structures exhibiting low intensities. Manual correction is very time-consuming and not suitable in clinical practice. This work presents a post-processing method for the automatic detection and closing of gaps in cerebrovascular segmentations. Methods: In this approach, the 3D centerline is calculated from an available vessel segmentation, which enables the detection of corresponding vessel endpoints. These endpoints are then used to detect possible connections to other 3D centerline voxels with a graph-based approach. After consistency check, reasonable detected paths are expanded to the vessel boundaries using a level set approach and combined with the initial segmentation. Results: For evaluation purposes, 100 gaps were artificially inserted at non-branching vessels and bifurcations in manual cerebrovascular segmentations derived from ten Time-of-Flight magnetic resonance angiography datasets. The results show that the presented method is capable of detecting 82% of the non-branching vessel gaps and 84% of the bifurcation gaps. The level set segmentation expands the detected connections with 0.42 mm accuracy compared to the initial segmentations. A further evaluation based on 10 real automatic segmentations from the same datasets shows that the proposed method detects 35 additional connections in average per dataset, whereas 92.7% were rated as correct by a medical expert. Conclusion: The presented approach can considerably improve the accuracy of cerebrovascular segmentations and of following analysis outcomes.

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Segmentation of Meristem Cells by an Automated Optimization Algorithm

Applied Sciences ◽

10.3390/app10238523 ◽

2020 ◽

Vol 10 (23) ◽

pp. 8523

Author(s):

Oswaldo Rojas ◽

Manuel G. Forero ◽

José M. Menéndez ◽

Angharad Jones ◽

Walter Dewitte ◽

...

Keyword(s):

Level Set ◽

Automatic Segmentation ◽

Optimization Method ◽

Intensity Level ◽

Low Contrast ◽

Segmentation Methods ◽

Segmented Images ◽

Optimization Function ◽

Confocal Images ◽

Automated Optimization

Meristem cells are irregularly shaped and appear in confocal images as dark areas surrounded by bright ones. Images are characterized by regions of very low contrast and absolute loss of edges deeper into the meristem. Edges are blurred, discontinuous, sometimes indistinguishable, and the intensity level inside the cells is similar to the background of the image. Recently, a technique called Parametric Segmentation Tuning was introduced for the optimization of segmentation parameters in diatom images. This paper presents a PST-tuned automatic segmentation method of meristem cells in microscopy images based on mathematical morphology. The optimal parameters of the algorithm are found by means of an iterative process that compares the segmented images obtained by successive variations of the parameters. Then, an optimization function is used to determine which pair of successive images allows for the best segmentation. The technique was validated by comparing its results with those obtained by a level set algorithm and a balloon segmentation technique. The outcomes show that our methodology offers better results than two free available state-of-the-art alternatives, being superior in all cases studied, losing 9.09% of the cells in the worst situation, against 75.81 and 25.45 obtained in the level set and the balloon segmentation techniques, respectively. The optimization method can be employed to tune the parameters of other meristem segmentation methods.

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Semi-Automatic Signature-Based Segmentation Method for Quantification of Neuromelanin in Substantia Nigra

Brain Sciences ◽

10.3390/brainsci9120335 ◽

2019 ◽

Vol 9 (12) ◽

pp. 335 ◽

Cited By ~ 1

Author(s):

Gašper Zupan ◽

Dušan Šuput ◽

Zvezdan Pirtošek ◽

Andrej Vovk

Keyword(s):

Substantia Nigra ◽

Sensitivity And Specificity ◽

Roc Analysis ◽

Automatic Segmentation ◽

High Sensitivity ◽

Segmentation Method ◽

Surface Sensitivity ◽

Volume Sensitivity ◽

Segmentation Methods ◽

The Difference

In Parkinson’s disease (PD), there is a reduction of neuromelanin (NM) in the substantia nigra (SN). Manual quantification of the NM volume in the SN is unpractical and time-consuming; therefore, we aimed to quantify NM in the SN with a novel semi-automatic segmentation method. Twenty patients with PD and twelve healthy subjects (HC) were included in this study. T1-weighted spectral pre-saturation with inversion recovery (SPIR) images were acquired on a 3T scanner. Manual and semi-automatic atlas-free local statistics signature-based segmentations measured the surface and volume of SN, respectively. Midbrain volume (MV) was calculated to normalize the data. Receiver operating characteristic (ROC) analysis was performed to determine the sensitivity and specificity of both methods. PD patients had significantly lower SN mean surface (37.7 ± 8.0 vs. 56.9 ± 6.6 mm2) and volume (235.1 ± 45.4 vs. 382.9 ± 100.5 mm3) than HC. After normalization with MV, the difference remained significant. For surface, sensitivity and specificity were 91.7 and 95 percent, respectively. For volume, sensitivity and specificity were 91.7 and 90 percent, respectively. Manual and semi-automatic segmentation methods of the SN reliably distinguished between PD patients and HC. ROC analysis shows the high sensitivity and specificity of both methods.

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Development of Semi-Automatic Segmentation Methods for Measuring Tibial Cartilage Volume

Digital Image Computing: Techniques and Applications (DICTA'05) ◽

10.1109/dicta.2005.26 ◽

2006 ◽

Cited By ~ 1

Author(s):

J. Cheong ◽

D. Suter ◽

F. Cicuttini

Keyword(s):

Automatic Segmentation ◽

Cartilage Volume ◽

Tibial Cartilage ◽

Segmentation Methods

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Research on Automatic Segmentation Methods of Multi-Beam Waterjet Cutting Process Drawings

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.314-316.1571 ◽

2011 ◽

Vol 314-316 ◽

pp. 1571-1575

Author(s):

Hui Kang Yang ◽

Dean Zhao ◽

Jin Liang Guo ◽

Jun Zhang ◽

Bo Chen

Keyword(s):

Automatic Segmentation ◽

Cutting Process ◽

Secondary Development ◽

Manual Segmentation ◽

Work Efficiency ◽

Waterjet Cutting ◽

Development Tool ◽

Segmentation Methods ◽

Low Efficiency

Currently, some manual segmentation problems exist in multi-beam waterjet cutting process drawings, such as low efficiency, incomplete segmentation and so on. In order to solve the problems, this paper designs a set of criteria for multi-beam cutting process and proposes the method of partition-classification trim, then uses the secondary development tool which is embedded in AutoCAD to program three user-defined commands, and these commands can partition the drawing by region, classify and trim the entities in the cutting process drawing. Through inputting the three simple commands on the command lines, it can realize automatic segmentation of cutting process drawings. Finally, the feasibility of this method is proved by a segmentation experiment. It can effectively solve the problems which exist in manual segmentation and greatly improve work efficiency.

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A HIGH VISUAL QUALITY SPRITE GENERATOR USING INTELLIGENT BLENDING WITHOUT SEGMENTATION MASKS

International Journal of Pattern Recognition and Artificial Intelligence ◽

10.1142/s0218001406005162 ◽

2006 ◽

Vol 20 (08) ◽

pp. 1139-1158 ◽

Cited By ~ 2

Author(s):

I-SHENG KUO ◽

LING-HWEI CHEN

Keyword(s):

Moving Objects ◽

Automatic Segmentation ◽

Visual Quality ◽

Experimental Result ◽

Feature Point Extraction ◽

Comparison Results ◽

Segmentation Methods ◽

Wu Method ◽

Better Than

The sprite generator introduced in MPEG-4 blends frames by averaging, which will make places, that are always occupied by moving objects, look blurred. Thus, providing segmented masks for moving objects is suggested. Several researchers have employed automatic segmentation methods to produce moving object masks. Based on these masks, they used a reliability-based blending strategy to generate sprites. Since perfect segmentation is impossible, some ghost-like shadows will appear in the generated sprite. To treat this problem, in this paper, an intelligent blending strategy without needing segmentation masks is proposed. It is based on the fact that for each point in the generated sprite, the corresponding pixels in most frames belong to background and only few belong to moving objects. A counting schema is provided to make only background points participate in average blending. The experimental result shows that the visual quality of the generated sprite using the proposed blending strategy is close to that using manually segmented masks and is better than that generated by Lu-Gao-Wu method. No ghostlike shadows are produced. Furthermore, a uniform feature point extraction method is proposed to increase the precision of global motion estimation, the effectiveness of this part is presented by showing the comparison results with other existing method.

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