Immersive Image Mining in Cardiology

Buried within the human body, the heart prohibits direct inspection, so most knowledge about heart failure is obtained by autopsy (in hindsight). Live immersive inspection within the human heart requires advanced data acquisition, image mining and virtual reality techniques. Computational sciences are being exploited as means to investigate biomedical processes in cardiology. IntraVascular UltraSound (IVUS) has become a clinical tool in recent several years. In this immersive data acquisition procedure, voluminous separated slice images are taken by a camera, which is pulled back in the coronary artery. Image mining deals with the extraction of implicit knowledge, image data relationships, or other patterns not explicitly stored in the image databases (Hsu, Lee, & Zhang, 2002). Human medical data are among the most rewarding and difficult of all biological data to mine and analyze, which has the uniqueness of heterogeneity and are privacy- sensitive (Cios & Moore, 2002). The goals of immersive IVUS image mining are providing medical quantitative measurements, qualitative assessment, and cardiac knowledge discovery to serve clinical needs on diagnostics, therapies, and safety level, cost and risk effectiveness etc.

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Immersive Image Mining in Cardiology

Encyclopedia of Data Warehousing and Mining ◽

10.4018/978-1-59140-557-3.ch111 ◽

2011 ◽

pp. 586-592

Author(s):

Xiaoqiang Liu ◽

Henk Koppelaar ◽

Ronald Hamers ◽

Nico Bruining

Keyword(s):

Heart Failure ◽

Virtual Reality ◽

Data Acquisition ◽

Human Body ◽

Human Heart ◽

Image Mining ◽

Computational Sciences ◽

Direct Inspection

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NOAA Image Data Acquisition to Determine Soil Moisture in Arequipa-Perú

IEEE Transactions on Nuclear Science ◽

10.1109/tns.2021.3087351 ◽

2021 ◽

pp. 1-1

Author(s):

A. Argume ◽

R. Coaguila ◽

P.R. Yanyachi ◽

J. Chilo

Keyword(s):

Soil Moisture ◽

Data Acquisition ◽

Image Data

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Payload Configurations for Efficient Image Acquisition – Indian Perspective

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprsarchives-xl-8-1201-2014 ◽

2014 ◽

Vol XL-8 ◽

pp. 1201-1206 ◽

Cited By ~ 1

Author(s):

D. R. M. Samudraiah ◽

M. Saxena ◽

S. Paul ◽

P. Narayanababu ◽

S. Kuriakose ◽

...

Keyword(s):

Remote Sensing ◽

Data Acquisition ◽

High Efficiency ◽

Image Acquisition ◽

Image Data ◽

Space Research ◽

Remotely Sensed Data ◽

Data Utilization ◽

Spectral Bands ◽

The World

The world is increasingly depending on remotely sensed data. The data is regularly used for monitoring the earth resources and also for solving problems of the world like disasters, climate degradation, etc. Remotely sensed data has changed our perspective of understanding of other planets. With innovative approaches in data utilization, the demands of remote sensing data are ever increasing. More and more research and developments are taken up for data utilization. The satellite resources are scarce and each launch costs heavily. Each launch is also associated with large effort for developing the hardware prior to launch. It is also associated with large number of software elements and mathematical algorithms post-launch. The proliferation of low-earth and geostationary satellites has led to increased scarcity in the available orbital slots for the newer satellites. Indian Space Research Organization has always tried to maximize the utility of satellites. Multiple sensors are flown on each satellite. In each of the satellites, sensors are designed to cater to various spectral bands/frequencies, spatial and temporal resolutions. Bhaskara-1, the first experimental satellite started with 2 bands in electro-optical spectrum and 3 bands in microwave spectrum. The recent Resourcesat-2 incorporates very efficient image acquisition approach with multi-resolution (3 types of spatial resolution) multi-band (4 spectral bands) electro-optical sensors (LISS-4, LISS-3* and AWiFS). The system has been designed to provide data globally with various data reception stations and onboard data storage capabilities. Oceansat-2 satellite has unique sensor combination with 8 band electro-optical high sensitive ocean colour monitor (catering to ocean and land) along with Ku band scatterometer to acquire information on ocean winds. INSAT- 3D launched recently provides high resolution 6 band image data in visible, short-wave, mid-wave and long-wave infrared spectrum. It also has 19 band sounder for providing vertical profile of water vapour, temperature, etc. The same system has data relay transponders for acquiring data from weather stations. The payload configurations have gone through significant changes over the years to increase data rate per kilogram of payload. Future Indian remote sensing systems are planned with very high efficient ways of image acquisition. <br><br> This paper analyses the strides taken by ISRO (Indian Space research Organisation) in achieving high efficiency in remote sensing image data acquisition. Parameters related to efficiency of image data acquisition are defined and a methodology is worked out to compute the same. Some of the Indian payloads are analysed with respect to some of the system/ subsystem parameters that decide the configuration of payload. Based on the analysis, possible configuration approaches that can provide high efficiency are identified. A case study is carried out with improved configuration and the results of efficiency improvements are reported. This methodology may be used for assessing other electro-optical payloads or missions and can be extended to other types of payloads and missions.

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The Sea Cucumber Holothuria (Halodeima) atra (Jager, 1833), in South Tarawa Lagoon (Republic of Kiribati): Environmental Variability, Population Biology and Fishing Pressure

10.26686/wgtn.16985467.v1 ◽

2021 ◽

Author(s):

◽

Teatim Tamaroa

Keyword(s):

Repeated Measures ◽

Population Biology ◽

Sea Cucumber ◽

Environmental Variability ◽

Preliminary Investigation ◽

Organic Matter Content ◽

Biological Data ◽

Qualitative Assessment ◽

Current Status ◽

Fishing Pressure

<p>Holothuria atra or lollyfish is the most common sea cucumber in the Pacific and Indian Oceans. The current status of Holothria atra at 13 sites of South Tarawa lagoon (Republic of Kiribati) was established by using biological surveys and fishers' questionnaires. A preliminary investigation was conducted in order to assess how and why environmental variability and fishing pressure have affected the spatial and temporal distribution, mean abundant and mean size of this species at the sites. The 13 sites were selected randomly, and marked with a GPS on the map of South Tarawa. Sedimentary characteristics were determined for each site, and a qualitative assessment of sites health was made. Lollyfish length, biomass and abundance and transect density were calculated for each site. The weight of organic matter content and size of sediment sample were determined. Data were analysed using Kruskal-Walis (KW) and Repeated measures (RM) ANOVA tests. This thesis shows that the environmental variability could not offer reasons as to why the biological data of lollyfish varied from one site to another. However, other factors that were tested may explain the variation in biological data. Fishing pressure is one of those parameters that can regulate the lollyfish distribution and density and responses from local fishers indicate that fishing pressure is high and that the lollyfish resource is under considerable harvest pressure. Dissolved oxygen concentration in the water column and in the sediment may be also involved in the variation in lollyfish distribution and density but this was not tested. The findings of this research lead to a number of recommendations for the sustainable harvest of lollyfish in Tarawa lagoon. These include consideration of gear restrictions, lollyfish size and number limits, and the establishment of marine protected areas under co-management arrangements.</p>

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Automated and Manual Quantification of Tumour Cellularity in Digital Slides for Tumour Burden Assessment

Scientific Reports ◽

10.1038/s41598-019-50568-4 ◽

2019 ◽

Vol 9 (1) ◽

Cited By ~ 5

Author(s):

Shazia Akbar ◽

Mohammad Peikari ◽

Sherine Salama ◽

Azadeh Yazdan Panah ◽

Sharon Nofech-Mozes ◽

...

Keyword(s):

Neural Networks ◽

Deep Neural Networks ◽

Traditional Approach ◽

Quantitative Measure ◽

Image Data ◽

Qualitative Assessment ◽

Residual Cancer Burden ◽

Automated Algorithms ◽

Tumour Cellularity

Abstract The residual cancer burden index is an important quantitative measure used for assessing treatment response following neoadjuvant therapy for breast cancer. It has shown to be predictive of overall survival and is composed of two key metrics: qualitative assessment of lymph nodes and the percentage of invasive or in situ tumour cellularity (TC) in the tumour bed (TB). Currently, TC is assessed through eye-balling of routine histopathology slides estimating the proportion of tumour cells within the TB. With the advances in production of digitized slides and increasing availability of slide scanners in pathology laboratories, there is potential to measure TC using automated algorithms with greater precision and accuracy. We describe two methods for automated TC scoring: 1) a traditional approach to image analysis development whereby we mimic the pathologists’ workflow, and 2) a recent development in artificial intelligence in which features are learned automatically in deep neural networks using image data alone. We show strong agreements between automated and manual analysis of digital slides. Agreements between our trained deep neural networks and experts in this study (0.82) approach the inter-rater agreements between pathologists (0.89). We also reveal properties that are captured when we apply deep neural network to whole slide images, and discuss the potential of using such visualisations to improve upon TC assessment in the future.

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Pattern Mining and Clustering on Image Databases

Successes and New Directions in Data Mining ◽

10.4018/978-1-59904-645-7.ch009 ◽

2008 ◽

pp. 187-212

Author(s):

Marinette Bouet ◽

Pierre Gançarski ◽

Marie-Aude Aufaure ◽

Omar Boussaïd

Keyword(s):

Pattern Mining ◽

Frequent Pattern Mining ◽

Image Data ◽

Research Direction ◽

Relevant Information ◽

Frequent Pattern ◽

Image Clustering ◽

Image Mining ◽

Clustering Methods ◽

New Research

Analysing and mining image data to derive potentially useful information is a very challenging task. Image mining concerns the extraction of implicit knowledge, image data relationships, associations between image data and other data or patterns not explicitly stored in the images. Another crucial task is to organize the large image volumes to extract relevant information. In fact, decision support systems are evolving to store and analyse these complex data. This paper presents a survey of the relevant research related to image data processing. We present data warehouse advances that organize large volumes of data linked with images and then, we focus on two techniques largely used in image mining. We present clustering methods applied to image analysis and we introduce the new research direction concerning pattern mining from large collections of images. While considerable advances have been made in image clustering, there is little research dealing with image frequent pattern mining. We shall try to understand why.

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A Study of the Accuracy of CyberKnife Spinal Radiosurgery Using Skeletal Structure Tracking

Operative Neurosurgery ◽

10.1227/01.neu.0000249248.55923.ec ◽

2007 ◽

Vol 60 (suppl_2) ◽

pp. ONS-147-ONS-156 ◽

Cited By ~ 45

Author(s):

Anthony K. Ho ◽

Dongshan Fu ◽

Cristian Cotrutz ◽

Steven L. Hancock ◽

Steven D. Chang ◽

...

Keyword(s):

Tracking System ◽

New Technology ◽

Image Data ◽

Error Component ◽

Qualitative Assessment ◽

Skeletal Structure ◽

Total System ◽

System Error ◽

Wide Range ◽

Spinal Radiosurgery

Abstract Objective: New technology has enabled the increasing use of radiosurgery to ablate spinal lesions. The first generation of the CyberKnife (Accuray, Inc., Sunnyvale, CA) image-guided radiosurgery system required implanted radiopaque markers (fiducials) to localize spinal targets. A recently developed and now commercially available spine tracking technology called Xsight (Accuray, Inc.) tracks skeletal structures and eliminates the need for implanted fiducials. The Xsight system localizes spinal targets by direct reference to the adjacent vertebral elements. This study sought to measure the accuracy of Xsight spine tracking and provide a qualitative assessment of overall system performance. Methods: Total system error, which is defined as the distance between the centroids of the planned and delivered dose distributions and represents all possible treatment planning and delivery errors, was measured using a realistic, anthropomorphic head-and-neck phantom. The Xsight tracking system error component of total system error was also computed by retrospectively analyzing image data obtained from eleven patients with a total of 44 implanted fiducials who underwent CyberKnife spinal radiosurgery. Results: The total system error of the Xsight targeting technology was measured to be 0.61 mm. The tracking system error component was found to be 0.49 mm. Conclusion: The Xsight spine tracking system is practically important because it is accurate and eliminates the use of implanted fiducials. Experience has shown this technology to be robust under a wide range of clinical circumstances.

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