Nigel J. B. McFarlane

Segmentation and tracking of piglets in images

An algorithm was developed for the segmentation and tracking of piglets and tested on a 200-image sequence of 10 piglets moving on a straw background. The image-capture rate was 1 image/140 ms. The segmentation method was a combination of image differencing with respect to a median background and a Laplacian operator. The features tracked were blob edges in the segmented image. During tracking, the piglets were modelled as ellipses initialised on the blobs. Each piglet was tracked by searching for blob edges in an elliptical window about the piglets position, which was predicted from its previous two positions.

Estimating Dimensions of Free-Swimming Fish Using 3D Point Distribution Models

Monitoring the growth of farmed fish is an important task which is currently difficult to carry out. An underwater stereo image analysis technique offers the potential for estimating key dimensions of free-swimming fish, from which the fish mass can be estimated. This paper describes the development of a three-dimensional point distribution model to capture the typical shape and variability of salmon viewed from the side. The model was fitted to stereo images of test fish by minimizing an energy function, which was based on probability distributions. The minimization was an iterated two-step method in which edges were selected for magnitude, direction, and proximity to the model, and the model was then fitted to the edges. A search strategy for locating the edges in 3D was devised. The model is tested on two image sets. In the first set 19 of the 26 fish are located in spite of their variable appearance and the presence of neighboring fish. In the second set the measurements made on 11 images of fish are compared with manual measurements of the fish dimensions and show an average error in length estimation of 5%.

Multimodal fusion of biomedical data at different temporal and dimensional scales

The introduction of integrative approaches to biomedical research (integrative biology, physiome, Virtual Physiological Human, etc.) poses original problems to computer aided medicine: the need to operate with large amounts of data that are strongly heterogeneous in structure, format and even in the knowledge domain that generated them; the need to integrate all of these data into a coherent whole; the further complication imposed by the fact that more and more frequently these data are captured at very different dimensional and/or temporal scales. The present study describes a first attempt at providing an interactive visualisation environment for homogeneous biomedical data defined over radically different spatial or temporal scales. In particular, we describe new strategies for the management of the dimensional information of highly heterogeneous data types; the management of temporal multiscaling; for 3D unstructured spatial multiscale visualisation and the related interaction paradigms and user interface. Preliminary results with a prototype implementation based on the OpenMAF application framework (http://www.openmaf.org) indicate that it is possible to develop effective environments for interactive visualisation of multiscale biomedical data.

Shape measurements of live pigs using 3-D image capture

A photogrammetric stereo imaging system was used to capture 3-D models of live pigs, and quantitative shape measurements were extracted from cross sections of the models. Stereo images were captured of 32 pigs, divided into high-lysine and low-lysine diet groups, and 3-D models were built from the images. Each pig was imaged once per week for 14 weeks. After slaughter, 10 of the pigs were dissected for muscle and fat measurements. A sequence of algorithms was applied to the 3-D models: differential geometry to reveal surface curvature features and detect the spine; manual landmark placement; fitting a curve to the spine; determining the vertical axis of the body; placing a slice plane across the abdomen close to the P2 position; extracting a cross section; and fitting a shape model to the cross section. Differential geometry revealed many qualitative features of the musculature. The spine was a line of minimum curvature along the back. The high-lysine pigs had higher height-to-width ratios and flatter backs than the low-lysine pigs. The dissected total muscle mass had a -0·66 correlation with the flatness-of-back shape parameter, and a 0·64 correlation with weight.

Fuzzy multicriteria decision-making for long cane pruning: A system for standard and complex vine configurations

Section I of this article presents the agronomic and technical purposes involved in vine pruning and the decision model used to simulate the pruners reasoning (fuzzy multicriteria decision making). Section II describes the method used for the choice of the best aggregation operator. Section III describes the model decision which is used to make automatic decision on complex vine configurations. Section IV presents the results: the model was performed on training set made of 140 standard pruning cases, 69.4% of similarity were observed between the decision model and the expert.

Visualization and simulated surgery of the left ventricle in the virtual pathological heart of the Virtual Physiological Human

Ischaemic heart failure remains a significant health and economic problem worldwide. This paper presents a user-friendly software system that will form a part of the virtual pathological heart of the Virtual Physiological Human (VPH2) project, currently being developed under the European Commission Virtual Physiological Human (VPH) programme. VPH2 is an integrated medicine project, which will create a suite of modelling, simulation and visualization tools for patient-specific prediction and planning in cases of post-ischaemic left ventricular dysfunction. The work presented here describes a three-dimensional interactive visualization for simulating left ventricle restoration surgery, comprising the operations of cutting, stitching and patching, and for simulating the elastic deformation of the ventricle to its post-operative shape. This will supply the quantitative measurements required for the post-operative prediction tools being developed in parallel in the same project.

Applying mesh conformation on shape analysis with missing data

A mesh conformation approach that makes use of deformable generic meshes has been applied to establishing correspondences between 3D shapes with missing data. Given a group of shapes with correspondences, we can build up a statistical shape model by applying principal component analysis (PCA). The conformation at first globally maps the generic mesh to the 3D shape based on manually located corresponding landmarks, and then locally deforms the generic mesh to clone the 3D shape. The local deformation is constrained by minimizing the energy of an elastic model. An algorithm was also embedded in the conformation process to fill missing surface data of the shapes. Using synthetic data, we demonstrate that the conformation preserves the configuration of the generic mesh and hence it helps to establish good correspondences for shape analysis. Case studies of the principal component analysis of shapes were presented to illustrate the successes and advantages of our approach.

Image-guidance for robotic harvesting of micropropagated plants

Abstract This paper describes a computer vision algorithm used to guide a laboratory robot in grasping the stems of micropropagated plants. The plants were chrysanthemums, growing in containers of agar, and were typical of plants ready for harvesting and dissection. The plants were imaged in silhouette. Pieces of stem were distinguished from other foliage by their thickness, length, angle-to-vertical, and connection downwards to the bottom of the container. These were combined to give, for each piece of stem, a measurement of the distance from the camera, and the estimated accuracy of the measurement. Experiments were conducted in which the stem segments were arranged in order of preference, depending on gripper clearance and the accuracy of the stereo measurement, and the tips of the grippers were guided to the most preferred segments. The amount of foliage affected the algorithm performance, and this varied between the plant clones. With the small-leaved clones, stems were identified with about 90% certainty, but with the large-leaved clones, very little detail could be seen in silhouette, and the performance was poor. The stereo measurement located the most preferred stems to within at least ±2 mm, and rarely resulted in the stem being missed or two stems being grasped. Failure to grasp a stem was mainly due to other foliage obstructing the grippers. The plants could not be pulled out of the container once grasped because the roots were too large. Recommendations for future work included more careful clearance checking and less bulky grippers to reduce the problems due to obstructing foliage, and improved image understanding to locate the bases of the plants, where they could be cut rather than pulled.

Visualisation of Left Ventricular Dysfunction in the Virtual Pathological Heart

While there has been significant progress in the treatment of ischemic heart failure, it remains a significant health and economic problem worldwide. In this paper, we present the challenges of modelling ischemic heart failure and introduce a user-friendly software system that will be a sub-set of the Virtual Pathological Heart environment which is currently being developed under the FP7 VPH2 project. This will provide patient-specific computational modelling and simulation of the human heart to assist the cardiologist and the cardiac surgeon in defining the severity and extent of disease in patients with post-ischemic Left Ventricular Dysfunction. The proposed system will provide visualisation tools for surgical assessment and planning: the registration and display of necrotic and hypo-kinetic regions; simulated surgical restoration (cutting and patching); and finally post-operative functional prediction (volume, shape and mitral valve regurgitation).

A stereo imaging system for the metric 3D recovery of porcine surface anatomy

We have succeeded in capturing porcine 3D surface anatomy in vivo by developing a high‐resolution stereo imaging system. The system achieved accurate 3D shape recovery by matching stereo pair images containing only natural surface textures at high (image) resolution. The 3D imaging system presented for pig shape capture is based on photogrammetry and comprises: stereo pair image acquisition, stereo camera calibration and stereo matching and surface and texture integration. Practical issues have been addressed, and in particular the integration of multiple range images into a single 3D surface. Robust image segmentation successfully isolated the pigs within the stereo images and was employed in conjunction with depth discontinuity detection to facilitate the integration process. The capture and processing chain is detailed here and the resulting 3D pig anatomy obtained using the system presented.