Haptic Curvature Comparison of Convex and Concave Shapes

A Convexity-Preserving Level-Set Method for the Segmentation of Tumor Organoids

Tumor organoid cultures play a crucial role in clinical practice, particularly in guiding medication by accurately determining the morphology and size of the organoids. However, segmenting individual tumor organoids is challenging due to their inhomogeneous internal intensity and overlapping structures. This paper proposes a convexity-preserving level-set segmentation 4 model based on the characteristics of tumor organoid images to segment individual tumor organoids precisely. Considering the predominant spherical shape exhibited by organoid growth, we propose a level-set model that includes a data-driven term, a curvature term, and a regularization term. The data-driven term pulls the contour to the vicinity of the boundary; the curvature term ensures the maintenance of convexity in the targeted segmentation, and the regularization term controls the smoothness and propagation of the contour. The proposed model aids in overcoming interference from factors such as overlap and noise, enabling the evolving curve to converge to the actual boundary of the target accurately. Furthermore, we propose a selectable and targeted initialization method that guarantees precise segmentation of specific regions of interest. Experiments on 51 pancreatic ductal adenocarcinoma organoid images show that our model achieved excellent segmentation results. The average Dice value and computation time are 98.81±0.48% and 20.67 s. Compared with the C-V and CPLSE models, it is more accurate and takes less time.

Convexity preserving level set for left ventricle segmentation

In clinical applications of cardiac left ventricle (LV) segmentation, the segmented LV is desired to include the cavity, trabeculae, and papillary muscles, which form a convex shape. However, the intensities of trabeculae and papillary muscles are similar to myocardium. Consequently, segmentation algorithms may easily misclassify trabeculae and papillary muscles as myocardium. In this paper, we propose a level set method with a convexity preserving mechanism to ensure the convexity of the segmented LV. In the proposed level set method, the curvature of the level set contours is used to control their convexity, such that the level set contour is finally deformed as a convex shape. The experimental results and the comparison with other level set methods show the advantage of our method in terms of segmentation accuracy. Compared with the state-of-the-art methods using deep-learning, our method is able to achieve comparable segmentation accuracy without the need for training, while the deep-learning based method requires a large set of training data and high-quality manual segmentation. Therefore, our method can be conveniently used in situation where training data and their manual segmentation are not available.

Haptic Rendering of 3D Geometry on 2D Touch Surface Based on Mechanical Rotation

In this paper, we present a robotic surface display that physically imitates the orientation of virtual 3D geometry touched through a 2D flat screen. The proposed approach renders the surface orientation of 3D geometry such that users can tactually obtain relative geometric information, which plays a significant role in the process of real-world haptic object perception. Taking advantage of the planar aspect of touch surfaces, the system constructs a rotation matrix to control the pose of a surface with minimal mechanical movements with given partial geometric information (i.e., normal vector at the point of touch). To evaluate the proposed rendering scheme, we conducted a geometric task (two alternative forced choices) with a set of hand-sized cylindrically curved geometries in which participants were asked to identify which of the two surfaces they perceived as being more curved. Curvatures with the same polarities (i.e., convex-convex and concave-concave) were employed in the study and psychometric curves estimated to obtain the threshold of the curvature difference and to validate the proposed rendering scheme. Possible applications of the proposed system and its limitations are also presented.

Two hands, one perception: how bimanual haptic information is combined by the brain

Humans routinely use both of their hands to gather information about shape and texture of objects. Yet, the mechanisms of how the brain combines haptic information from the two hands to achieve a unified percept are unclear. This study systematically measured the haptic precision of humans exploring a virtual curved object contour with one or both hands to understand if the brain integrates haptic information from the two hemispheres. Bayesian perception theory predicts that redundant information from both hands should improve haptic estimates. Thus exploring an object with two hands should yield haptic precision that is superior to unimanual exploration. A bimanual robotic manipulandum passively moved the hands of 20 blindfolded, right-handed adult participants along virtual curved contours. Subjects indicated which contour was more “curved” (forced choice) between two stimuli of different curvature. Contours were explored uni- or bimanually at two orientations (toward or away from the body midline). Respective psychophysical discrimination thresholds were computed. First, subjects showed a tendency for one hand to be more sensitive than the other with most of the subjects exhibiting a left-hand bias. Second, bimanual thresholds were mostly within the range of the corresponding unimanual thresholds and were not predicted by a maximum-likelihood estimation (MLE) model. Third, bimanual curvature perception tended to be biased toward the motorically dominant hand, not toward the haptically more sensitive left hand. Two-handed exploration did not necessarily improve haptic sensitivity. We found no evidence that haptic information from both hands is integrated using a MLE mechanism. Rather, results are indicative of a process of “sensory selection”, where information from the dominant right hand is used, although the left, nondominant hand may yield more precise haptic estimates.

A kinematic cue for active haptic shape perception

This study quantitatively investigates the actual movements that observers make when exploring a shape. It addresses the question of how the kinematics of these movements relate to and may affect perceived shape. It is one of the first studies to do so for real stimuli and for relatively unconstrained exploration. Observers discriminated the curvature of circularly shaped strips. We identify a kinematic cue for a single finger stroking across circular strips under conditions of slip. This cue consists of two terms that are related to the shift of the skin contact surface across the fingertip and the rotation angle of the finger. The rotation angle of the finger is found to increase linearly with the curvature of the stimulus. Observers rotated their finger less on a concave curvature by a constant amount, while at the same time they overestimated the radius of the concave strips compared to the convex ones. We show that responses were related to kinematic properties of the actual movements and we consider several mechanisms that could explain this finding.

Curvature affects haptic length perception

One possible way of haptically perceiving length is to trace a path with one's index finger and estimate the distance traversed. Here, we present an experiment in which observers judge the lengths of paths across cylindrically curved surfaces. We found that convex and concave surfaces had qualitatively different effects: convex lengths were overestimated, whereas concave lengths were underestimated. In addition, we observed that the index finger moved more slowly across the convex surface than across the concave one. As a result, movement times for convex lengths were longer. The considerable correlation between movement times and length estimates suggests that observers take the duration of movement as their primary measure of perceived length, but disregard movement speeds. Several mechanisms that could underlie observers' failure to account for speed differences are considered.

Using curvature information in haptic shape perception of 3D objects

Are humans able to perceive the circularity of a cylinder that is grasped by the hand? This study presents the findings of an experiment in which cylinders with a circular cross-section had to be distinguished from cylinders with an elliptical cross-section. For comparison, the ability to distinguish a square cuboid from a rectangular cuboid was also investigated. Both elliptical and rectangular shapes can be characterized by the aspect ratio, but elliptical shapes also contain curvature information. We found that an elliptical shape with an aspect ratio of only 1.03 could be distinguished from a circular shape both in static and dynamic touch. However, for a rectangular shape, the aspect ratio needed to be about 1.11 for dynamic touch and 1.15 for static touch in order to be discernible from a square shape. We conclude that curvature information can be employed in a reliable and efficient manner in the perception of 3D shapes by touch.

Transfer of the curvature aftereffect in dynamic touch

A haptic curvature aftereffect is a phenomenon in which the perception of a curved shape is systematically altered by previous contact to curvature. In the present study, the existence and intermanual transfer of curvature aftereffects for dynamic touch were investigated. Dynamic touch is characterized by motion contact between a finger and a stimulus. A distinction was made between active and passive contact of the finger on the stimulus surface. We demonstrated the occurrence of a dynamic curvature aftereffect and found a complete intermanual transfer of this aftereffect, which suggests that dynamically obtained curvature information is represented at a high level. In contrast, statically perceived curvature information is mainly processed at a level that is connected to a single hand, as previous studies indicated. Similar transfer effects were found for active and passive dynamic touch, but a stronger aftereffect was obtained when the test surface was actively touched. We conclude that the representation of object information depends on the exploration mode that is used to acquire information.