A Haptic Interaction Technique for Volume Images Based on Gradient Diffusion

Vidholm, Erik; Nyström, Ingela

doi:10.1109/whc.2005.11

Cited by 12 publications

(4 citation statements)

References 11 publications

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“…A common type of haptic feedback is force based on the local gradient, in this case the voxel values near the pointer [6]. The gradient force propelled the haptic device (a penlike object) toward a region of higher intensity or resisted the movement of the pen from a region of higher intensity.…”

Section: Methodsmentioning

confidence: 99%

Will haptic feedback speed up medical imaging? An application to radiation treatment planning

Anderlind¹,

Noz²,

Sallnäs³

et al. 2008

Acta Oncologica

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Section: Methodsmentioning

confidence: 99%

Will haptic feedback speed up medical imaging? An application to radiation treatment planning

Anderlind¹,

Noz²,

Sallnäs³

et al. 2008

Acta Oncologica

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“…The combination of stereo graphics and haptics was proposed in [24] in order to facilitate the seeding procedure that enables the user to trace vessels in a better way during semiautomatic segmentation of MRI images. A haptic interaction technique based on gradient vector flow (GVF) was proposed in [25] for navigation in 3D images. It enables the operator to remain centered inside objects by providing haptic feedback on the boundaries.…”

Section: Haptic Segmentationmentioning

confidence: 99%

Fast and accurate semiautomatic haptic segmentation of brain tumor in 3D MRI images

Latifinavid¹,

Bilen²,

Konukseven³

et al. 2016

Turk J Elec Eng & Comp Sci

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Abstract:In this study, a novel virtual reality-based interactive method combined with the application of a graphical processing unit (GPU) is proposed for the semiautomatic segmentation of 3D magnetic resonance imaging (MRI) of the brain. The key point of our approach is to use haptic force feedback guidance for the selection of seed points in a bounded volume with similar intensity and gradient. For the automatic determination of a bounded volume of segmentation in real time, parallel computation on the GPU is used. Automatic segmentation is applied in this adjustable bounded spherical volume with a variable diameter, which is controlled according to the edge map acquired from the gradient map. The haptic force feedback is used in order to guide the user to remain in a volume, where the intensity and gradient change are under a defined threshold range. After each seed point selection, the segmentation algorithm works inside the bounded volume of the ball with an adjusted diameter. The proposed segmentation method based on force and visual feedback with the advantage of adjustable bounded volume is not only accurate and effective in narrow spaces near the boundaries of different layers, but also fast in large homogeneous spaces since the radius of the ball increases in such regions. Parallel programming on the GPU is used for computing gradient change in selected directions, which is needed for the self-adjustment of the sphere diameter. Gradient values are used for calculating the haptic force on the CPU in real time. In this study, two haptic devices are used, one for getting haptic force feedback and the other for camera guidance during 3D visualization. A comparison between manual segmentation of MRI by an expert surgeon and the proposed segmentation algorithm is done. The proposed segmentation procedure is completed 4 times faster than the manual segmentation with similar accuracy.

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“…Currently, haptically enhanced interaction mainly relies on magnetic effects [Oakley et al 2000], or as a gradient force all over the environment [Vidholm and Nystrom 2005]. When applied to menu interaction, haptics seem to bring benefits [Komerska and Ware 2004], but in some cases haptics can also decrease performances for example in terms of task selection times [Oakley et al 2001].…”

Section: Introductionmentioning

confidence: 99%

HardBorders

Essert

Capobianco

2009

Proceedings of the 16th ACM Symposium on Virtual Reality Software and Technology

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In this paper, we introduce a 3D menu with a new technique of haptic guidance, for virtual environments. The 3D menu consists in a thin polyhedral shape, with the items at the corners. The HardBorders technique haptically simulates the collisions of the pointer with the borders of the polyhedron, making it glide towards the items of the menu. A comparison with 2 reference modalities has been performed, showing a clear advantage of our HardBorders technique.

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A Haptic Interaction Technique for Volume Images Based on Gradient Diffusion

Cited by 12 publications

References 11 publications

Will haptic feedback speed up medical imaging? An application to radiation treatment planning

Will haptic feedback speed up medical imaging? An application to radiation treatment planning

Fast and accurate semiautomatic haptic segmentation of brain tumor in 3D MRI images

HardBorders

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