Multiresolution Moment Filters: Theory and Applications

We introduce local weighted geometric moments that are computed from an image within a sliding window at multiple scales. When the window function satisfies a two-scale relation, we prove that lower order moments can be computed efficiently at dyadic scales by using a multiresolution wavelet-like algorithm. We show that B-splines are well-suited window functions because, in addition to being refinable, they are positive, symmetric, separable, and very nearly isotropic (Gaussian shape). We present three applications of these multiscale local moments. The first is a feature-extraction method for detecting and characterizing elongated structures in images. The second is a noise-reduction method which can be viewed as a multiscale extension of Savitzky-Golay filtering. The third is a multiscale optical-flow algorithm that uses a local affine model for the motion field, extending the Lucas-Kanade optical-flow method. The results obtained in all cases are promising

Entropy in Image Analysis II

Image analysis is a fundamental task for any application where extracting information from images is required. The analysis requires highly sophisticated numerical and analytical methods, particularly for those applications in medicine, security, and other fields where the results of the processing consist of data of vital importance. This fact is evident from all the articles composing the Special Issue "Entropy in Image Analysis II", in which the authors used widely tested methods to verify their results. In the process of reading the present volume, the reader will appreciate the richness of their methods and applications, in particular for medical imaging and image security, and a remarkable cross-fertilization among the proposed research areas

해마 하위 영역 CA1과 CA3의 시각 자극 변화에 따른 장소 표상 패턴 연구

학위논문(박사) -- 서울대학교대학원 : 자연과학대학 뇌인지과학과, 2023. 2. 이인아.우리가 일상에서 경험하는 사건들은 하나의 스토리로 구성되어 일화 기억으로 형성된다. 해마는 과거에 경험한 일 들 뿐만 아니라 현재 경험하고 있는 사건들에 대한 일화 기억을 처리할 때 필수적인 뇌 영역이라고 알려져 있다. 설치류의 해마에서 관찰되는 장소 세포는 해마가 동물이 인지하고 있는 공간에 대한 지도를 형성하는 핵심적인 역할을 하는 것으로 알려져 있다. 특히 특정한 공간에서만 선별적으로 발화하는 장소 세포는 환경에 변화가 주어졌을 때 remapping이라는 현상으로 환경의 변화를 반영한다고 알려져 있다. 환경에 변화가 있을 때, 장소 세포가 동일한 위치에서 활동하며 발화 빈도를 조정하거나 전혀 다른 장소에서 활동하는 패턴으로 관찰된다. 이러한 장소 세포의 변화는 i) 기존의 기억을 조금 변형하거나, ii) 새로운 기억을 형성하는 일화 기억의 형태를 가지고 있다. 하지만 장소 세포가 불규칙적인 패턴으로 공간의 변화를 표상함에 따라 이들의 활동이 갖는 의미는 불분명하게 남아있다. 또한 장소 세포가 복합적인 감각 정보들을 반영한다는 특징은, 이들이 어떤 인지적 의미를 가지며 활동을 하는 것인지에 대한 난제를 남겼다. 본인은 해마의 장소 세포가 일화 기억에 어떤 기여를 할 것인지, 특히 변화된 환경에서 무엇을 새로 기억하고 기존에 알고 있는 정보는 어떻게 처리할 것인지 연산하는 과정을 해마의 하위 영역인 CA1과 CA3에서 각각 어떻게 표상하는지 알아보고자 하였다. 이에 대한 답을 찾기 위해 본인은 동물이 상호작용하며 경험할 수 있는 가상 현실 (VR) 시스템을 제작하여 가상 환경의 시각 자극을 정량적으로 조작하였다. 이 과정에서 본인은 동물이 경험하는 시각 자극의 변화와 (i.e., input) 해마 장소세포의 전기적 활동 (i.e., output) 간의 관계를 조사하였다. 첫 번째 질문으로는 본인이 구축한 가상 현실 시스템에서 장소 세포가 발현되는지를 확인하였다. 그 결과로 기존 문헌에서 보고되었던 결과와 비슷한 수준의 장소 세포들을 검증할 수 있었다. 본인이 구축한 가상 현실 시스템에서 장소 세포가 관찰된다는 것을 확인한 이후에는, 기존 환경에 정량적인 시각적 변화를 주어 장소 세포가 해당 변화를 어떻게 반영하는지 질문하였다. 그 결과로, 해마의 하위 영역 CA1에서 기존 환경에 대한 표상을 유지하는 집단과, 특정 환경에 변화가 가해진 사건에 의해 새로운 표상을 유지하는 집단이 동시다발적으로 나뉜다는 현상을 관찰하였다. 반면, 해마 하위 영역인 CA3에서는 환경에 변화가 이루어졌음에도 불구하고 대부분의 장소 세포들이 기존 환경에 대한 표상을 유지하였다. 이러한 결과를 토대로 해마 하위 영역인 CA3은 기존에 알고 있던 환경에 대한 기억을 안정적으로 유지하는 역할을 수행하는 반면, 해마 하위 영역인 CA1은 변화하는 환경 내에서도 이전의 기억과 새로운 기억을 독립적으로 구분하여 새로운 정보를 유연하게 학습하도록 하는 가능성을 제시하고자 한다.Any events or experiences in the given space and time are stitched together as an episode. The hippocampus has been widely acknowledged for its role in episodic memory for decades. At the same time, the rodent hippocampus exhibits the salient feature where its principal neurons are active in a spatially selective pattern (i.e., place cell). The place cells change their firing patterns as there are changes in the environments. Until now, we have been interpreting these firing changes, also known as "remapping," to have a functional significance in episodic memory by i) slightly modifying the old map to retrieve subtle changes from the previous memory or ii) forming the new map to reflect any major changes. In the real world, place cells receive complex sensory information from multiple sources, including multimodal sensory inputs and idiothetic information, making it even more challenging to interpret place cell activity from the intermingled sensory inputs fed into the hippocampal system. Taking advantage of the virtual reality (VR) system, I investigated how the hippocampal subregions CA1 and CA3 networks reflect environmental change. Thereby, I parametrically manipulated the environment by adding visual noise (i.e., virtual fog) in the VR environment and examined how hippocampal place cells in the CA1 and CA3 responded as visual noises were added to the environment in a quantified manner. Prior studies have suggested that CA3 forms a discrete map of the modified environments, presumably by performing either pattern separation or pattern completion. However, place cells in CA1 exhibit less coherent responses to environmental changes compared to CA3. This discrepancy between the CA1 and CA3 subregions is puzzling because CA3 output must pass through the CA1 area before reaching cortical areas. Furthermore, the functional roles of the CA1 in processing the environmental changes still need to be investigated due to the heterogeneous neural outputs with mixed yet conflicting findings. I first questioned whether our VR system reliably induced the place cells from both hippocampal subregions CA1 and CA3. As a result, I observed that the firing properties of hippocampal place cells are equivalent to that reported in the previous studies. Once I confirmed that visual environments in our VR system dominantly controlled the place cells, I examined how place cells in the CA1 and CA3 subregions responded to various levels of changes made to the visual environment. As visual noise was introduced to the familiar environment, I found that place cells in CA1 split simultaneously into two subpopulations: In one, place cells with old maps while changing their firing rate to reflect noise levels (i.e., rate remapping); in another, place cells with new maps to differentiate the dynamically changing environment from an old stable environment (i.e., global remapping). The place cells in CA3 mainly sustained the old map and reflected noise levels by rate remapping. Suppose one considers the rate remapping class of place cells as pattern-completing cells and the global remapping class as pattern-separating cells. In that case, the CA1 can manifest both pattern separation and pattern completion classes of neurons at the environmental change. My dissertation suggests that CA1 can simultaneously form an orthogonal map of the same environment to remember new episodes without interfering with the old memory.Background 1 Anatomical structures of the Hippocampal system and their proposed roles 2 The remapping properties of Hippocampal place cell 7 The usage of the virtual reality (VR) system for rodents in studying the hippocampus 16 Chapter 1. Visual scene stimulus exerts dominant control over the place fields 19 Introduction 20 Materials and methods 22 Results 37 Discussion 53 Chapter 2. The functional role of the CA1 and CA3 in processing the visually modified environment 56 Introduction 57 Materials and methods 59 Results 63 Discussion 94 General Discussion 98 Bibliography 111 국문초록 137박

Neural mechanisms of binocular motion in depth perception

Motion in depth (MID) can be cued by two binocular sources of information. These are changes in retinal disparity over time (changing disparity, CD), and binocular opponent velocity vectors (inter-ocular velocity difference, IOVD). This thesis presents a series of psychophysical and fMRI experiments investigating the neural pathways supporting the perception of CD and IOVD. The first two experiments investigated how CD and IOVD mechanisms draw on information encoded in the magnocellular, parvocellular and koniocellular pathways. The chromaticity of CD and IOVD-isolating stimuli was manipulated to bias activity in these three pathways. Although all stimulus types and chromaticities supported a MID percept, fMRI revealed an especially dominant koniocellular contribution to the IOVD mechanism. Because IOVD depends on eye-specific velocity signals, experiment three sought to identify an area in the brain that encodes motion direction and eye of origin information. Classification and multivariate pattern analysis techniques were applied to fMRI data, but no area where both types of information were present simultaneously was identified. Results suggested that IOVD mechanisms inherit eye-specific information from V1. Finally, experiment four asked whether activity elicited by CD and IOVD stimuli could also be modulated by an attentional task where participants were asked to detect changes in MID or local contrast. fMRI activity was strongly modulated by attentional state, and activity in motion-selective areas was predictive of whether participants correctly identified the change in CD or IOVD MID. This suggests that these areas contain populations of neurons that are crucial for detecting, and behaviourally responding to, both types of MID. The work presented in this thesis detail a thorough investigation of the neural pathways that underlie the computation of CD and IOVD cues to MID

NBS monograph

From Introduction: "This report is the first of a series intended to provide a selective overview of research and development efforts and requirements in the somewhat overlapping fields of the computer and information sciences and technologies. The projected series of reports will attempt to outline the probable range of R & D activities in the computer and information sciences and technologies through selective reviews of the literature and to develop a reasonable consensus with respect to the opinions of workers in these and potentially related fields as to areas of continuing R & D concern for research program planning or review in these areas.

Pacific Symposium on Biocomputing 2023

The Pacific Symposium on Biocomputing (PSB) 2023 is an international, multidisciplinary conference for the presentation and discussion of current research in the theory and application of computational methods in problems of biological significance. Presentations are rigorously peer reviewed and are published in an archival proceedings volume. PSB 2023 will be held on January 3-7, 2023 in Kohala Coast, Hawaii. Tutorials and workshops will be offered prior to the start of the conference.PSB 2023 will bring together top researchers from the US, the Asian Pacific nations, and around the world to exchange research results and address open issues in all aspects of computational biology. It is a forum for the presentation of work in databases, algorithms, interfaces, visualization, modeling, and other computational methods, as applied to biological problems, with emphasis on applications in data-rich areas of molecular biology.The PSB has been designed to be responsive to the need for critical mass in sub-disciplines within biocomputing. For that reason, it is the only meeting whose sessions are defined dynamically each year in response to specific proposals. PSB sessions are organized by leaders of research in biocomputing's 'hot topics.' In this way, the meeting provides an early forum for serious examination of emerging methods and approaches in this rapidly changing field

Very High Resolution (VHR) Satellite Imagery: Processing and Applications

Recently, growing interest in the use of remote sensing imagery has appeared to provide synoptic maps of water quality parameters in coastal and inner water ecosystems;, monitoring of complex land ecosystems for biodiversity conservation; precision agriculture for the management of soils, crops, and pests; urban planning; disaster monitoring, etc. However, for these maps to achieve their full potential, it is important to engage in periodic monitoring and analysis of multi-temporal changes. In this context, very high resolution (VHR) satellite-based optical, infrared, and radar imaging instruments provide reliable information to implement spatially-based conservation actions. Moreover, they enable observations of parameters of our environment at greater broader spatial and finer temporal scales than those allowed through field observation alone. In this sense, recent very high resolution satellite technologies and image processing algorithms present the opportunity to develop quantitative techniques that have the potential to improve upon traditional techniques in terms of cost, mapping fidelity, and objectivity. Typical applications include multi-temporal classification, recognition and tracking of specific patterns, multisensor data fusion, analysis of land/marine ecosystem processes and environment monitoring, etc. This book aims to collect new developments, methodologies, and applications of very high resolution satellite data for remote sensing. The works selected provide to the research community the most recent advances on all aspects of VHR satellite remote sensing

Advanced Sensing and Image Processing Techniques for Healthcare Applications

This Special Issue aims to attract the latest research and findings in the design, development and experimentation of healthcare-related technologies. This includes, but is not limited to, using novel sensing, imaging, data processing, machine learning, and artificially intelligent devices and algorithms to assist/monitor the elderly, patients, and the disabled population