Automatic Summarization of Changes in Biological Image Sequences Using Algorithmic Information Theory

An algorithmic information-theoretic method is presented for object-level summarization of meaningful changes in image sequences. Object extraction and tracking data are represented as an attributed tracking graph (ATG). Time courses of object states are compared using an adaptive information distance measure, aided by a closed-form multidimensional quantization. The notion of meaningful summarization is captured by using the gap statistic to estimate the randomness deficiency from algorithmic statistics. The summary is the clustering result and feature subset that maximize the gap statistic. This approach was validated on four bioimaging applications: 1) It was applied to a synthetic data set containing two populations of cells differing in the rate of growth, for which it correctly identified the two populations and the single feature out of 23 that separated them; 2) it was applied to 59 movies of three types of neuroprosthetic devices being inserted in the brain tissue at three speeds each, for which it correctly identified insertion speed as the primary factor affecting tissue strain; 3) when applied to movies of cultured neural progenitor cells, it correctly distinguished neurons from progenitors without requiring the use of a fixative stain; and 4) when analyzing intracellular molecular transport in cultured neurons undergoing axon specification, it automatically confirmed the role of kinesins in axon specification.     

On Providing Support for Protocol Adaptation in Mobile Wireless Networks

The availability of variety of communication devices offers a choice among networks with vastly different characteristics. No single protocol or application can be expected to perform well over all these networks. A mobile host is likely to encounter these different networks and needs to adapt accordingly. The problem of adapting to a changing network environment is further complicated, because changes in network conditions are usually transparent to higher layers of the protocol stack. In order to allow automatic adaptation of applications and protocols, awareness of link conditions and network environment is necessary. In this paper, we present a uniform mechanism based on ICMP messages for providing information about the environment to the protocol stack. We also show how protocols can adapt to changes in the environment, and in particular, demonstrate dynamic fine tuning of some of the well known protocols such as UDP and TCP. Performance measurements demonstrate that our framework imposes little overheads and improves protocol performance under changing network conditions.     

A computational model for C. elegans locomotory behavior: application to multiworm tracking.

A computational approach is presented for modeling and quantifying the structure and dynamics of the nematode C. elegans observed by time-lapse microscopy. Worm shape and conformations are expressed in a decoupled manner. Complex worm movements are expressed in terms of three primitive patterns--peristaltic progression, deformation, and translation. The model has been incorporated into algorithms for segmentation and simultaneous tracking of multiple worms in a field, some of which may be interacting in complex ways. A recursive Bayesian filter is used for tracking. Unpredictable behaviors associated with interactions are resolved by multiple-hypothesis tracking. Our algorithm can track worms of diverse sizes and conformations (coiled/uncoiled) in the presence of imaging artifacts and clutter, even when worms are overlapping with others. A two-observer performance assessment was conducted over 16 image sequences representing wild-type and uncoordinated mutants as a function of worm size, conformation, presence of clutter, and worm entanglement. Overall detected tracking failures were 1.41%, undetected tracking failures were 0.41%, and segmentation errors were 1.11% of worm length. When worms overlap, our method reduced undetected failures from 12% to 1.75%, and segmentation error from 11% to 5%. Our method provides the basis for reliable morphometric and locomotory analysis of freely behaving worm populations.     

Integrated services packet networks with mobile hosts: Architecture and performance

This paper considers the support of real-time services to mobile users in an Integrated Services Packet Network. In the currently existing architectures, the service guarantees provided to the mobile hosts are mobility dependent, i.e., mobile hosts experience wide variation in the quality of service and often service disruption when hosts move from one location to another. The network performance degrades significantly when mobile hosts are provided with mobility independent service guarantees. In this paper we have proposed a service model for mobile hosts that can support adaptive applications which can withstand service degradation and disruption, as well as applications which require mobility independent service guarantees. We describe an admission control scheme for implementing this service model and evaluate its performance by simulation experiments. Simulation results show that, if sufficient degree of multiplexing of the mobility dependent and independent services are allowed, the network does not suffer any significant performance degradation and in particular our admission control scheme achieves high utilization of network resources.     

Embedding torus on the star graph

In this paper, we present a scheme for efficient embedding of torus of any dimension on a star graph. The dilation of the embedding is four. The expansion is small. Congestion depends upon the routing scheme used. With one routing scheme, the congestion is bound by a small constant (≈2) with an increase in expansion cost. For a second routing scheme, the congestion is O(n), for an n-star, with bounded expansion     

The dual-bootstrap iterative closest point algorithm with application to retinal image registration

Motivated by the problem of retinal image registration, this paper introduces and analyzes a new registration algorithm called Dual-Bootstrap Iterative Closest Point (Dual-Bootstrap ICP). The approach is to start from one or more initial, low-order estimates that are only accurate in small image regions, called bootstrap regions. In each bootstrap region, the algorithm iteratively: 1) refines the transformation estimate using constraints only from within the bootstrap region; 2) expands the bootstrap region; and 3) tests to see if a higher order transformation model can be used, stopping when the region expands to cover the overlap between images. Steps 1): and 3), the bootstrap steps, are governed by the covariance matrix of the estimated transformation. Estimation refinement [Step 2)] uses a novel robust version of the ICP algorithm. In registering retinal image pairs, Dual-Bootstrap ICP is initialized by automatically matching individual vascular landmarks, and it aligns images based on detected blood vessel centerlines. The resulting quadratic transformations are accurate to less than a pixel. On tests involving approximately 6000 image pairs, it successfully registered 99.5% of the pairs containing at least one common landmark, and 100% of the pairs containing at least one common landmark and at least 35% image overlap.     

MRSVP: A Resource Reservation Protocol for an Integrated Services Network with Mobile Hosts

This paper describes a reservation protocol to provide real-time services to mobile users in an Integrated Services Packet Network. Mobility of hosts has significant impact on the quality of service provided to a real-time application. The currently proposed network system architecture and mechanisms to provide real-time services to fixed hosts are inadequate to accommodate the mobile hosts which can frequently change their point of attachments to the fixed network. Mobile hosts may experience wide variations of quality of service due to mobility. To reduce the impacts of mobility on QoS guarantees, a mobile host needs to make advance resource reservations at multiple locations it may possibly visit during the lifetime of the connection. The currently proposed reservation protocol in the Internet, RSVP, is not adequate to make such reservations for mobile hosts. In this paper, we describe a new reservation protocol, MRSVP, for supporting integrated services in a network with mobile hosts.     

Score level fusion of voting strategy of geometric hashing and SURF for an efficient palmprint-based identification

This paper proposes an efficient indexing scheme for palmprint-based identification system. The proposed system uses geometric hashing of SURF key-points to index the palmprint into hash table and makes score level fusion of voting strategy based on geometric hashing and SURF score to identify the live palmprint. All ordered pairs of SURF key-points of the palmprint are scaled and mapped to a predefined coordinate system and all other points are similarity transformed. The new location after transformation serves as the index of the hash table. During identification, all ordered pairs of key-points of live palmprint are scaled and mapped to the coordinate system while remaining points are similarity transformed. A vote is casted to all images in the corresponding bins. Images having votes more than certain threshold are considered as candidate images of the live palmprint. SURF features of the live palmprint and the candidate images are compared for matching. Matching scores which are based on SURF key-points and vote of the corresponding candidate image are fused using weighted sum rule. The candidate image with the highest fused score is considered as the best match. The system is tested on IITK, CASIA and PolyU datasets. It has been observed that penetration rate of the proposed system is less than 30% for 0% bin miss rate (BMR) and has the identification accuracy of more than 97% for all three datasets. Further, the system is evaluated for robustness on downscaled and rotated. It has been found that the identification accuracy of the system for top best match is more than 90% for images downscaled up to 49% and accuracy is more than 85% when images are rotated at any angle.     

A framework for delivering multicast messages in networks with mobile hosts

To accommodatemobile hosts (MHs) within existing data networks, the static network is augmented with mobile support stations (MSSs) that communicate directly with MHs, usually via wireless links. Connectivity of the overall network changes dynamically as MHs connect to the static network from different locations (MSSs) at different times. Compared to their desktop counterparts, mobile hosts face a new set of constraints namely, low bandwith of the wireless links, tight constraints on power consumption and a significantly lower computing capability. Thus, even without considering failures, integration of mobile computer within existing networks pose a new set of problems. In this paper, we look at the problems associated with delivering multicast meassages to mobile hosts. First, we identify how a mobile host's ability to connect to different MSSs at different times, affects delivery of multicast messages and present schemes to deliver multicast messages to MHs fromatleast-one location, fromatmost-one location, and fromexactly-one location. Next, we introduce multicast groups of mobile hosts wherein each multicast group is associated with a host view, a set of MSSs representing theaggregate location information of the group. A host-view membership algorithm is then presented and combined with the multicast scheme for exactly-once delivery. As a result, to deliver a multicast message to a specified group, copies of the message need be propagated only to the MSSs in the group's host-view.This work was done while the author was a graduate student at Rutgers University.This research work was supported in part by ARPA under contract number DAAH04-95-1-0596, NSF grant numbers CCR 95-09620, IRIS 95-09816 and sponsors of WINLAB.