Image databases: Problems and perspectives

With the increasing number of computer graphics, image processing, and pattern recognition applications, economical storage, efficient representation and manipulation, and powerful and flexible query languages for retrieval of image data are of paramount importance. These and related issues pertinent to image data bases are examined

VolumeEVM: A new surface/volume integrated model

Volume visualization is a very active research area in the field of scien-tific visualization. The Extreme Vertices Model (EVM) has proven to be a complete intermediate model to visualize and manipulate volume data using a surface rendering approach. However, the ability to integrate the advantages of surface rendering approach with the superiority in visual exploration of the volume rendering would actually produce a very complete visualization and edition system for volume data. Therefore, we decided to define an enhanced EVM-based model which incorporates the volumetric information required to achieved a nearly direct volume visualization technique. Thus, VolumeEVM was designed maintaining the same EVM-based data structure plus a sorted list of density values corresponding to the EVM-based VoIs interior voxels. A function which relates interior voxels of the EVM with the set of densities was mandatory to be defined. This report presents the definition of this new surface/volume integrated model based on the well known EVM encoding and propose implementations of the main software-based direct volume rendering techniques through the proposed model.Postprint (published version

Types of Digital Visuals in E-Learning

This session explores the various types of digital visuals used in e-learning, with examples covering one-dimensional to four-dimensional imagery. Examples will demonstrate how the addition of live data, time elements, image overlays, digital-enabled effects, and interactivity add value to electronic learning. Samples from live courses and sites will be shown. There will be a discussion of how the various types of images can be developed

PICTOGRAM ON SIGNAGE AS AN EFFECTIVE COMMUNICATION

Pictograms on signage may convey information or convey regulatory and prohibitory which are easily understood briefly by visitors from any circles. Problems identified is Museum of Lampung does not currently have a pictogram on any signage. Therefore, the design of pictograms on signage for the Museum of Lampung is important to communicate information briefly and effectively. This study use qualitative and quantitative approach. Literature review; observation to three similar museums, interview and questionnaires are conducted to collect data. Three similar objects are compared to get analysis data. The result shows that the pictogram is one of the informative signage elements that are important to clarify the information without having to read the text.  This study proposes pictogram on signage for the Museum of Lampung with a visual concept by adopting identity of Lampung i.e. siger and tapis pattern. The aim of this study is to show the importance of using pictograms in graphic communication. It is expected the effective pictogram on signage will be able to communicate the necessary information and easy to understand immediately without using a lot of text

A study of spatial data models and their application to selecting information from pictorial databases

People have always used visual techniques to locate information in the space surrounding them. However with the advent of powerful computer systems and user-friendly interfaces it has become possible to extend such techniques to stored pictorial information. Pictorial database systems have in the past primarily used mathematical or textual search techniques to locate specific pictures contained within such databases. However these techniques have largely relied upon complex combinations of numeric and textual queries in order to find the required pictures. Such techniques restrict users of pictorial databases to expressing what is in essence a visual query in a numeric or character based form. What is required is the ability to express such queries in a form that more closely matches the user's visual memory or perception of the picture required. It is suggested in this thesis that spatial techniques of search are important and that two of the most important attributes of a picture are the spatial positions and the spatial relationships of objects contained within such pictures. It is further suggested that a database management system which allows users to indicate the nature of their query by visually placing iconic representations of objects on an interface in spatially appropriate positions, is a feasible method by which pictures might be found from a pictorial database. This thesis undertakes a detailed study of spatial techniques using a combination of historical evidence, psychological conclusions and practical examples to demonstrate that the spatial metaphor is an important concept and that pictures can be readily found by visually specifying the spatial positions and relationships between objects contained within them

Mesh and Pyramid Algorithms for Iconic Indexing

In this paper parallel algorithms on meshes and pyramids for iconic indexing are presented. Our algorithms are asymptotically superior to previously known parallel algorithms

A Study of FPGA Resource Utilization for Pipelined Windowed Image Computations

In image processing operations, each pixel is often treated independently and operated upon by using values of other pixels in the neighborhood. These operations are often called windowed image computations (or neighborhood operations). In this thesis, we examine the implementation of a windowed computation pipeline in an FPGA-based environment. Typically, the image is generated outside the FPGA environment (such as through a camera) and the result of the windowed computation is consumed outside the FPGA environment (for example, in a screen for display or an engine for higher level analysis). The image is typically large (over a million pixels 1000×1000 image) and the FPGA input-output (I/O) infrastructure is quite modest in comparison (typically a few hundred pins). Consequently, the image is brought into the chip a small piece (tile) at a time. We define a handshaking scheme that allows us to construct an FPGA architecture without making large assumptions about component speeds and synchronization. We define a pipeline architecture for windowed computations, including details of a stage to accommodate FPGA pin-limitation and bounded storage. We implement a design to better suit FPGAs where it ensures a smoother (stall-resistant) flow of the computation in the pipeline. Based on the architecture proposed, we have analytically predicted resource usage in the FPGA. In particular, we have shown that for an N×N image processed as n×n tiles on a z-stage windowed computation with parameter w; θ(n^2+log⁡N+log⁡z ) pins are used and θ(n^2 z) memory is used. We ran simulations that validated these predictions on two FPGAs (Artix-7 and Kintex-7) with different resources. As we had predicted, the pins and distributed memory turned out to be the most used resources. Our simulations have also shown that the operating clock speed of the design is relatively independent of the number of stages in the pipeline; this is in line with what was expected with the handshaking scheme that isolates the timing of communicating modules. Our work, although aimed at FPGAs, could also be applied to any I/O pin-limited devices and memory limited environments

개 흉부 방사선 자료의 딥러닝 적용을 통한 심장 면적 자동 분석 방법 개발

학위논문 (석사) -- 서울대학교 대학원 : 보건대학원 보건학과, 2021. 2. 성주헌 .Introduction : Measurement of canine heart size in thoracic lateral radiograph is crucial in detecting heart enlargement caused by diverse cardiovascular diseases. The purpose of this study was 1) to develop deep learning (DL) model that segments heart and 4th thoracic vertebrae (T4) body, 2) develop new radiographic measurement using calculated 2 dimensional heart area and length of T4 body, and 3) calculate performance of our new measurement to detect heart enlargement using echocardiographic measurement as gold standard. Methods : Total 1,000 thoracic radiographic images of dog were collected from Seoul National University Veterinary Medicine Teaching Hospital from 2018. 01. 01 to 2020. 08. 31. Given ground truth mask, two Attention U-Nets for segmentation of heart and T4 body were trained using different hyperparameters. Among 1,000 images, model was trained with 800 images, validated with 100 images and tested with 100 images. Performance of DL model was assessed with dice score coefficient, precision and recall. New calculation method was developed to calculate heart volume and adjust by T4 body length, which was named vertebra-adjusted heart volume (VaHV). Correlation of VaHV of 100 test images and reported VHS (vertebral heart score) was assessed. With 188 images with concurrent echocardiographic examination, diagnostic performance of VaHV for detecting cardiomegaly was assessed by students t-test, receiver operating characteristic (ROC) curve and area under the curve (AUC). Results : The two trained DL model showed very good similarity with ground truth (dice score coefficient 0.956 for heart segmentation, 0.844 for T4 body segmentation). VaHV of 100 test images showed statistically significant correlation with VHS. VaHV showed better diagnostic performance in detecting left atrial enlargement and left ventricular enlargement than VHS. Conclusions : DL model can be used to segment heart and vertebrae in veterinary radiographic images. Our new radiographic measurement obtained from DL model can potentially be used to assess and monitor cardiomegaly in dogs.개의 심장질환 중 가장 높은 유병률을 나타내는 이첨판 폐쇄부전증을 포함하여 다양한 심장질환이 점진적인 심비대를 특징으로 하기에, 개의 흉부 방사선 영상에서 심장 크기를 측정하여 심비대를 진단하는 것은 심장질환을 조기에 발견하고 적절한 치료시기를 계획하는 데 있어 매우 중요한 부분을 차지한다. 현장에서 바로 잴 수 있는 지표로서 기존에는 vertebral heart score (VHS)가 널리 사용되고 있으나, 이는 1차원 길이의 합으로 이루어진 지표이기에 심비대를 진단하는 데 한계가 있을 수 있다. 본 연구의 목적은 개의 흉부 방사선 영상에서 심장 면적과 척추체 길이를 자동으로 산출하는 딥러닝 모델을 구축하고, 이를 이용하여 심장 용적을 추정할 수 있는 지표를 개발하는 것이었다. 본 연구는 서울대학교 수의과대학 동물병원 검진자료로부터 수집된 총 1,188 건의 자료를 바탕으로 수행되었다. 1,000건의 영상은 심장과 척추체의 면적을 자동으로 분할 (semantic segmentation) 해주는 딥러닝 모델을 훈련시키고 평가하기 위해 사용되었으며, 이를 이용하여 새로운 심장 용적 지표인 vertebra-adjusted heart volume (VaHV) 를 산출했다. 추가로 1달 미만 간격의 방사선 촬영 기록과 심장초음파 검진 기록을 가진 188건의 영상을 수집하여 훈련된 딥러닝 모델을 이용해 계산한 VaHV와 심장초음파 기록 (LA/Ao, LVIDDN) 을 비교하여 VaHV의 심비대 진단능을 평가하였다. 심장과 척추체의 면적 불균형을 보완하기 위해 서로 다른 hyperparameter를 가진 Improved Attention U-Net이 사용되었으며, 두 개의 신경망 모두 시험용 데이터셋에서 정답 면적과 높은 일치율 (dice score coefficient 0.956, 0.844) 를 보였으며, 신경망의 예측결과에서 계산된 VaHV는 기존에 기록된 VHS와 통계적으로 유의한 상관계수를 (r = 0.69, P 1.6, LVIDDN > 1.7) 에 대해 높은 예측력을 가짐을 확인하였으며 (AUC 0.818), 기존에 사용되던 VHS의 예측력 (AUC 0.805) 보다 우수한 성능을 보임을 확인하였다. 본 연구는 수의방사선에서 최초로 딥러닝을 이용한 의미론적 면적 분할 (semantic segmentation) 을 적용하여 수의 영상에서 기존보다 더 다양한 신경망 알고리즘이 활용될 수 있는 가능성을 보여주었다. 또한 심장의 2차원 면적이 심비대를 진단함에 있어 기존의 길이 기반 심장 크기 측정 지표를 보완할 수 있다는 가능성을 보여주었다.1. Introduction 6 2. Materials and Methods 8 2.1 Data Collection 8 2.2 Development of DL model 10 2.2.1 Introduction to Semantic Segmentation 10 2.2.2 Attention U-Net with Focal Tversky Loss, Surface Loss 11 2.2.2.1 Attention U-Net 11 2.2.2.2 Improved Attention U-Net with Focal Tversky Loss 12 2.2.2.3 Surface Loss 14 2.2.3 Image Preprocessing 15 2.2.4 Establishing Ground Truth 16 2.2.5 Training DL Model 16 2.2.5.1 DL Model for Heart Segmentation 18 2.2.5.2 DL Model for T4 Body Segmentation 19 2.3 Volumetric Measurement of Heart 20 2.3.1 Analysis of Binary Mask 20 2.3.2 Vertebra-adjusted Heart Volume (VaHV) 21 2.3.3 Calculation of VaHV from DL Model Prediction 22 2.4 Statistical Methods 23 2.4.1 Segmentation DL Model Performance 23 2.4.2 Correlation between VaHV and VHS 23 2.4.3 Evaluation of Cardiomegaly using Echocardiographic Measurement 23 3. Results 24 3.1 DL Model 24 3.1.1 Heart Segmentation 24 3.1.2 T4 Body Segmentation 26 3.2 Descriptive Statistics of VaHV 28 3.3 Correlation between VaHV and VHS 29 3.4 Diagnostic Performance of VaHV for Detecting Cardiomegaly 30 4. Discussion 33 5. Conclusion 34 6. References 35 초록 38Maste