Computer-based automated left atrium segmentation and volumetry from ECG-gated coronary CT angiography data. Comparison with manual slice segmentation and ultrasound planimetric methods

Energy Technology Data Exchange (ETDEWEB)

Bauer, R.W.; Kraus, B.; Kerl, J.M.; Lehnert, T.; Vogl, T.J. [Universitaetsklinikum Frankfurt (Germany). Inst. fuer Diagnostische und Interventionelle Radiologie; Bernhardt, D.; Vega-Higuera, F. [Siemens AG, Healthcare Sector, Forchheim (Germany). Computed Tomography; Ackermann, H. [Universitaetsklinikum Frankfurt (Germany). Inst. fuer Biostatistik und Mathematische Modellierung

2010-12-15

Purpose: Enlargement of the left atrium is a risk factor for cardiovascular or cerebrovascular events. We evaluated the performance of prototype software for fully automated segmentation and volumetry of the left atrium. Materials and Methods: In 34 retrospectively ECG-gated coronary CT angiography scans, the end-systolic (LAVsys) and end-diastolic (LAVdia) volume of the left atrium was calculated fully automatically by prototype software. Manual slice segmentation by two independent experienced radiologists served as the reference standard. Furthermore, two independent observers calculated the LAV utilizing two ultrasound planimetric methods ('area length' and 'prolate ellipse') on CTA images. Measurement periods were compared for all methods. Results: The left atrial volumes calculated with the prototype software were in excellent agreement with the results from manual slice segmentation (r = 0.97 - 0.99; p < 0.001; Bland-Altman) with excellent interobserver agreement between both radiologists (r = 0.99; p < 0.001). Ultrasound planimetric methods clearly showed a higher variation (r = 0.72 - 0.86) with moderate interobserver agreement (r = 0.51 - 0.79). The measurement period was significantly lower with the software (267 {+-} 28 sec; p < 0.001) than with ultrasound methods (431 {+-} 68 sec) or manual slice segmentation (567 {+-} 91 sec). Conclusion: The prototype software showed excellent agreement with manual slice segmentation with the least time consumption. This will facilitate the routine assessment of the LA volume from coronary CTA data and therefore risk stratification. (orig.)

Operating manual for the Bulk Shielding Reactor

International Nuclear Information System (INIS)

1983-04-01

The BSR is a pool-type reactor. It has the capabilities of continuous operation at a power level of 2 MW or at any desired lower power level. This manual presents descriptive and operational information. The reactor and its auxillary facilities are described from physical and operational viewpoints. Detailed operating procedures are included which are applicable from source-level startup to full-power operation. Also included are procedures relative to the safety of personnel and equipment in the areas of experiments, radiation and contamination control, emergency actions, and general safety. This manual supercedes all previous operating manuals for the BSR

Operating manual for the Bulk Shielding Reactor

International Nuclear Information System (INIS)

1987-03-01

The BSR is a pool-type reactor. It has the capabilities of continuous operation at a power level of 2 MW or at any desired lower power level. This manual presents descriptive and operational information. The reactor and its auxiliary facilities are described from physical and operational viewpoints. Detailed operating procedures are included which are applicable from source-level startup to full-power operation. Also included are procedures relative to the safety of personnel and equipment in the areas of experiments, radiation and contamination control, emergency actions, and general safety. This manual supersedes all previous operating manuals for the BSR

Operating manual for the Bulk Shielding Reactor

Energy Technology Data Exchange (ETDEWEB)

1987-03-01

The BSR is a pool-type reactor. It has the capabilities of continuous operation at a power level of 2 MW or at any desired lower power level. This manual presents descriptive and operational information. The reactor and its auxiliary facilities are described from physical and operational viewpoints. Detailed operating procedures are included which are applicable from source-level startup to full-power operation. Also included are procedures relative to the safety of personnel and equipment in the areas of experiments, radiation and contamination control, emergency actions, and general safety. This manual supersedes all previous operating manuals for the BSR.

Operating manual for the Bulk Shielding Reactor

Energy Technology Data Exchange (ETDEWEB)

1983-04-01

The BSR is a pool-type reactor. It has the capabilities of continuous operation at a power level of 2 MW or at any desired lower power level. This manual presents descriptive and operational information. The reactor and its auxillary facilities are described from physical and operational viewpoints. Detailed operating procedures are included which are applicable from source-level startup to full-power operation. Also included are procedures relative to the safety of personnel and equipment in the areas of experiments, radiation and contamination control, emergency actions, and general safety. This manual supercedes all previous operating manuals for the BSR.

Prostate segmentation by feature enhancement using domain knowledge and adaptive region based operations

International Nuclear Information System (INIS)

Nanayakkara, Nuwan D; Samarabandu, Jagath; Fenster, Aaron

2006-01-01

Estimation of prostate location and volume is essential in determining a dose plan for ultrasound-guided brachytherapy, a common prostate cancer treatment. However, manual segmentation is difficult, time consuming and prone to variability. In this paper, we present a semi-automatic discrete dynamic contour (DDC) model based image segmentation algorithm, which effectively combines a multi-resolution model refinement procedure together with the domain knowledge of the image class. The segmentation begins on a low-resolution image by defining a closed DDC model by the user. This contour model is then deformed progressively towards higher resolution images. We use a combination of a domain knowledge based fuzzy inference system (FIS) and a set of adaptive region based operators to enhance the edges of interest and to govern the model refinement using a DDC model. The automatic vertex relocation process, embedded into the algorithm, relocates deviated contour points back onto the actual prostate boundary, eliminating the need of user interaction after initialization. The accuracy of the prostate boundary produced by the proposed algorithm was evaluated by comparing it with a manually outlined contour by an expert observer. We used this algorithm to segment the prostate boundary in 114 2D transrectal ultrasound (TRUS) images of six patients scheduled for brachytherapy. The mean distance between the contours produced by the proposed algorithm and the manual outlines was 2.70 ± 0.51 pixels (0.54 ± 0.10 mm). We also showed that the algorithm is insensitive to variations of the initial model and parameter values, thus increasing the accuracy and reproducibility of the resulting boundaries in the presence of noise and artefacts

Requirements to be met by the operation manual

International Nuclear Information System (INIS)

1981-03-01

The rule applies to the contents and the lay-out of the operating manual for stationary nuclear power plants. The draft contains: 1. General requirement to be met by the contents of the operating manual. The operating manual to be arranged in 4 parts (part 1: internal rules and regulations; part 2: operation overall plant; part 3: incidents; part 4: operation systems). Safety specifications to be included in the manual, the exemption being the system of technical documentation. 2. General requirements to be met by the lay-out of the operating manual. Comprehensibility; legibility; structure and subdivisions; arrangement of the instructions and design of the manuals cover. 3. Requirements to be met by part 1. Defining the various internal rules and regulations (personnel management); rules and regulations concerning inspections and shift work; maintenance and repair; radiation protection; guard duty and admission; alarm; fire protection; first aid. 4. Requirements to be met by part 2. Provisions and operational limitations; limit values important from the point of view of safety; normal operation; anomalous operation; in-service inspections. 6. Requirements to be met by part 3. 7. Annex: Rules, regulations and stipulations mentioned in the rule draft. (orig.)

CT-based patient modeling for head and neck hyperthermia treatment planning: manual versus automatic normal-tissue-segmentation.

Science.gov (United States)

Verhaart, René F; Fortunati, Valerio; Verduijn, Gerda M; van Walsum, Theo; Veenland, Jifke F; Paulides, Margarethus M

2014-04-01

Clinical trials have shown that hyperthermia, as adjuvant to radiotherapy and/or chemotherapy, improves treatment of patients with locally advanced or recurrent head and neck (H&N) carcinoma. Hyperthermia treatment planning (HTP) guided H&N hyperthermia is being investigated, which requires patient specific 3D patient models derived from Computed Tomography (CT)-images. To decide whether a recently developed automatic-segmentation algorithm can be introduced in the clinic, we compared the impact of manual- and automatic normal-tissue-segmentation variations on HTP quality. CT images of seven patients were segmented automatically and manually by four observers, to study inter-observer and intra-observer geometrical variation. To determine the impact of this variation on HTP quality, HTP was performed using the automatic and manual segmentation of each observer, for each patient. This impact was compared to other sources of patient model uncertainties, i.e. varying gridsizes and dielectric tissue properties. Despite geometrical variations, manual and automatic generated 3D patient models resulted in an equal, i.e. 1%, variation in HTP quality. This variation was minor with respect to the total of other sources of patient model uncertainties, i.e. 11.7%. Automatically generated 3D patient models can be introduced in the clinic for H&N HTP. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

CT-based patient modeling for head and neck hyperthermia treatment planning: Manual versus automatic normal-tissue-segmentation

International Nuclear Information System (INIS)

Verhaart, René F.; Fortunati, Valerio; Verduijn, Gerda M.; Walsum, Theo van; Veenland, Jifke F.; Paulides, Margarethus M.

2014-01-01

Background and purpose: Clinical trials have shown that hyperthermia, as adjuvant to radiotherapy and/or chemotherapy, improves treatment of patients with locally advanced or recurrent head and neck (H and N) carcinoma. Hyperthermia treatment planning (HTP) guided H and N hyperthermia is being investigated, which requires patient specific 3D patient models derived from Computed Tomography (CT)-images. To decide whether a recently developed automatic-segmentation algorithm can be introduced in the clinic, we compared the impact of manual- and automatic normal-tissue-segmentation variations on HTP quality. Material and methods: CT images of seven patients were segmented automatically and manually by four observers, to study inter-observer and intra-observer geometrical variation. To determine the impact of this variation on HTP quality, HTP was performed using the automatic and manual segmentation of each observer, for each patient. This impact was compared to other sources of patient model uncertainties, i.e. varying gridsizes and dielectric tissue properties. Results: Despite geometrical variations, manual and automatic generated 3D patient models resulted in an equal, i.e. 1%, variation in HTP quality. This variation was minor with respect to the total of other sources of patient model uncertainties, i.e. 11.7%. Conclusions: Automatically generated 3D patient models can be introduced in the clinic for H and N HTP

The EADC-ADNI Harmonized Protocol for manual hippocampal segmentation on magnetic resonance

DEFF Research Database (Denmark)

Frisoni, Giovanni B; Jack, Clifford R; Bocchetta, Martina

2015-01-01

BACKGROUND: An international Delphi panel has defined a harmonized protocol (HarP) for the manual segmentation of the hippocampus on MR. The aim of this study is to study the concurrent validity of the HarP toward local protocols, and its major sources of variance. METHODS: Fourteen tracers segme...

State Energy Program Operations Manual

Energy Technology Data Exchange (ETDEWEB)

Office of Building Technology, State and Community Programs

1999-03-17

The State Energy Program Operations Manual is a reference tool for the states and the program officials at the U.S. Department of Energy's Office of Building Technology, State and Community Programs and Regional Support Offices as well as State Energy Offices. The Manual contains information needed to apply for and administer the State Energy Program, including program history, application rules and requirements, and program administration and monitoring requirements.

Associations Between Family Adversity and Brain Volume in Adolescence: Manual vs. Automated Brain Segmentation Yields Different Results

Directory of Open Access Journals (Sweden)

Hannah Lyden

2016-09-01

Full Text Available Associations between brain structure and early adversity have been inconsistent in the literature. These inconsistencies may be partially due to methodological differences. Different methods of brain segmentation may produce different results, obscuring the relationship between early adversity and brain volume. Moreover, adolescence is a time of significant brain growth and certain brain areas have distinct rates of development, which may compromise the accuracy of automated segmentation approaches. In the current study, 23 adolescents participated in two waves of a longitudinal study. Family aggression was measured when the youths were 12 years old, and structural scans were acquired an average of 4 years later. Bilateral amygdalae and hippocampi were segmented using three different methods (manual tracing, FSL, and NeuroQuant. The segmentation estimates were compared, and linear regressions were run to assess the relationship between early family aggression exposure and all three volume segmentation estimates. Manual tracing results showed a positive relationship between family aggression and right amygdala volume, whereas FSL segmentation showed negative relationships between family aggression and both the left and right hippocampi. However, results indicate poor overlap between methods, and different associations between early family aggression exposure and brain volume depending on the segmentation method used.

Associations between Family Adversity and Brain Volume in Adolescence: Manual vs. Automated Brain Segmentation Yields Different Results.

Science.gov (United States)

Lyden, Hannah; Gimbel, Sarah I; Del Piero, Larissa; Tsai, A Bryna; Sachs, Matthew E; Kaplan, Jonas T; Margolin, Gayla; Saxbe, Darby

2016-01-01

Associations between brain structure and early adversity have been inconsistent in the literature. These inconsistencies may be partially due to methodological differences. Different methods of brain segmentation may produce different results, obscuring the relationship between early adversity and brain volume. Moreover, adolescence is a time of significant brain growth and certain brain areas have distinct rates of development, which may compromise the accuracy of automated segmentation approaches. In the current study, 23 adolescents participated in two waves of a longitudinal study. Family aggression was measured when the youths were 12 years old, and structural scans were acquired an average of 4 years later. Bilateral amygdalae and hippocampi were segmented using three different methods (manual tracing, FSL, and NeuroQuant). The segmentation estimates were compared, and linear regressions were run to assess the relationship between early family aggression exposure and all three volume segmentation estimates. Manual tracing results showed a positive relationship between family aggression and right amygdala volume, whereas FSL segmentation showed negative relationships between family aggression and both the left and right hippocampi. However, results indicate poor overlap between methods, and different associations were found between early family aggression exposure and brain volume depending on the segmentation method used.

Industrial Assessment Center (IAC) Operations Manual

Energy Technology Data Exchange (ETDEWEB)

Gopalakrishnan, Bhaskaran [West Virginia Univ., Morgantown, WV (United States); Nimbalkar, Sachin U. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Wenning, Thomas J. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Thirumaran, Kiran [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

2017-04-01

IAC Operations Manual describes organizational model and operations of the Industrial Assessment Center (IAC), Center management activities, typical process of energy assessment, and energy assessment data for specific industry sectors.

IFRS 8 Operating Segments - A Closer Look

OpenAIRE

Muthupandian, K S

2008-01-01

The International Accounting Standards Board issued the International Financial Reporting Standard 8 Operating Segments. Segment information is one of the most vital aspects of financial reporting for investors and other users. The IFRS 8 requires an entity to adopt the ‘management approach’ to reporting on the financial performance of its operating segments. This article presents a closer look of the standard (objective, scope, and disclosures).

Hanford Environmental Information System (HEIS) Operator`s Manual. Volume 1

Energy Technology Data Exchange (ETDEWEB)

Schreck, R.I.

1991-10-01

The Hanford Environmental Information System (HEIS) is a consolidated set of automated resources that effectively manage the data gathered during environmental monitoring and restoration of the Hanford Site. The HEIS includes an integrated database that provides consistent and current data to all users and promotes sharing of data by the entire user community. This manual describes the facilities available to the operational user who is responsible for data entry, processing, scheduling, reporting, and quality assurance. A companion manual, the HEIS User`s Manual, describes the facilities available-to the scientist, engineer, or manager who uses the system for environmental monitoring, assessment, and restoration planning; and to the regulator who is responsible for reviewing Hanford Site operations against regulatory requirements and guidelines.

Operation manual for the core flow test loop zone power-supply controller

Energy Technology Data Exchange (ETDEWEB)

Harper, R.E.

1981-11-01

The core flow test loop, which is part of the Gas-Cooled Fast Breeder Reactor Program (GCFR) at ORNL, is a high-pressure, high-temperature, out-of-reactor helium circulation system that is being constructed to permit study of the performance at steady-state and transient conditions of simulated segments of core assemblies for a GCFR demonstration plant. The simulated core segments, which are divided into zones, contain electrical heating elements to simulate the heat generated by fission. To control the power which is applied to a zone, a novel multitapped transformer and zone power control system have been designed and built which satisfy stringent design criteria. The controller can match power output to demand to within better than +-1% over a 900:1 dynamic range and perform full-power transients within 1 s. The power is applied in such a way as to minimize the electromagnetic interference at the bandwidth of the loop instrumentation, and the controller incorporates several error detection techniques, making it inherently fail-safe. The operation manual describes the specifications, operating instructions, error detection capabilities, error recovery, troubleshooting, calibration and QA procedures, and maintenance requirements. Also included are sections on the theory of operation, circuitry description, and a complete set of schematics.

Manually operated coded switch

International Nuclear Information System (INIS)

Barnette, J.H.

1978-01-01

The disclosure related to a manually operated recodable coded switch in which a code may be inserted, tried and used to actuate a lever controlling an external device. After attempting a code, the switch's code wheels must be returned to their zero positions before another try is made

Automatic segmentation of vertebrae from radiographs

DEFF Research Database (Denmark)

Mysling, Peter; Petersen, Peter Kersten; Nielsen, Mads

2011-01-01

Segmentation of vertebral contours is an essential task in the design of automatic tools for vertebral fracture assessment. In this paper, we propose a novel segmentation technique which does not require operator interaction. The proposed technique solves the segmentation problem in a hierarchical...... is constrained by a conditional shape model, based on the variability of the coarse spine location estimates. The technique is evaluated on a data set of manually annotated lumbar radiographs. The results compare favorably to the previous work in automatic vertebra segmentation, in terms of both segmentation...

Operating manual for the Health Physics Research Reactor

International Nuclear Information System (INIS)

1985-11-01

This manual is intended to serve as a guide in the operation and maintenance of the Health Physics Researh Reactor (HPRR) of the Health Physics Dosimetry Applications Research (DOSAR) Facility. It includes descriptions of the HPRR and of associated equipment such as the reactor positioning devises and the derrick. Procedures for routine operation of the HPRR are given in detail, and checklists for the various steps are provided where applicable. Emergency procedures are similarly covered, and maintenance schedules are outlined. Also, a bibliography of references giving more detailed information on the DOSAR Facility is included. Changes to this manual will be approved by at least two of the following senior staff members: (1) the Operations Division Director, (2) the Reactor Operations Department Head, (3) the Supervisor of Reactor Operations TSF-HPRR Areas. The master copy and the copy of the manual issued to the HPRR Operations Supervisor will always reflect the latest revision. 22 figs

C-TIC Console Operator's User Manual

Science.gov (United States)

1996-07-01

The C-TIC Console Operator's User Manual is designed to assist the operator at : the Corridor Transportation Information Center with the navigation and use of : the application programs in the C-TIC. This document will concentrate solely on : the ext...

Operating Manual of Helium Refrigerator (Rev. 2)

Energy Technology Data Exchange (ETDEWEB)

Song, K.M.; Son, S.H.; Kim, K.S.; Lee, S.K.; Kim, M.S. [Korea Electric Power Research Institute, Taejon (Korea)

2002-07-01

A helium refrigerator was installed as a supplier of 20K cold helium to the cryogenic distillation system of WTRF pilot plant. The operating procedures of the helium refrigerator, helium compressor and auxiliary apparatus are described for the safety and efficient operation in this manual. The function of the helium refrigerator is to remove the impurities from the compressed helium of about 250psig, to cool down the helium from ambient temperature to 20K through the heat exchanger and expansion engine and to transfer the cold helium to the cryogenic distillation system. For the smoothly operation of helium refrigerator, the preparation, the start-up, the cool-down and the shut-down of the helium refrigerator are described in this operating manual. (author). 3 refs., 14 tabs.

Spent Nuclear Fuel Project Cold Vacuum Drying Facility Operations Manual

International Nuclear Information System (INIS)

IRWIN, J.J.

1999-01-01

This document provides the Operations Manual for the Cold Vacuum Drying Facility (CVDF). The Manual was developed in conjunction with HNF-553, Spent Nuclear Fuel Project Final Safety Analysis Report Annex B--Cold Vacuum Drying Facility. The HNF-SD-SNF-DRD-002, 1999, (Cold Vacuum Drying Facility Design Requirements), Rev. 4. and the CVDF Final Design Report. The Operations Manual contains general descriptions of all the process, safety and facility systems in the CVDF, a general CVD operations sequence and references to the CVDF System Design Descriptions (SDDs). This manual has been developed for the SNFP Operations Organization and shall be updated, expanded, and revised in accordance with future design, construction and startup phases of the CVDF until the CVDF final ORR is approved

33 CFR 385.28 - Operating Manuals.

Science.gov (United States)

2010-07-01

... Processes § 385.28 Operating Manuals. (a) General provisions. (1) The Corps of Engineers and the non-Federal... emergencies that can be expected to occur at a project are: drowning and other accidents, failure of the operation facilities, chemical spills, treatment plant failures and other temporary pollution problems...

Different approaches to synovial membrane volume determination by magnetic resonance imaging: manual versus automated segmentation

DEFF Research Database (Denmark)

Østergaard, Mikkel

1997-01-01

Automated fast (5-20 min) synovial membrane volume determination by MRI, based on pre-set post-gadolinium-DTPA enhancement thresholds, was evaluated as a substitute for a time-consuming (45-120 min), previously validated, manual segmentation method. Twenty-nine knees [rheumatoid arthritis (RA) 13...

Multi-canister overpack operations and maintenance manual

International Nuclear Information System (INIS)

PIERCE, S.R.

1999-01-01

This manual provides general operating and maintenance instructions for the Multi-Canister Overpack. Procedure outlines included are conceptual in nature and will be modified, expanded, and refined during preparation of detailed operating procedures

COE1 Calorimeter Operations Manual

Energy Technology Data Exchange (ETDEWEB)

Santi, Peter Angelo [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2015-12-15

The purpose of this manual is to describe the operations of the COE1 calorimeter which is used to measure the thermal power generated by the radioactive decay of plutonium-bearing materials for the purposes of assaying the amount of plutonium within the material.

Dounreay Shuffler diagnostic software operations manual

International Nuclear Information System (INIS)

Eccleston, G.W.; Stuewe, B.; Klosterbuer, S.; Van Lyssel, T.

1985-07-01

This operations manual describes the test software for the Dounreay Shuffler. The Shuffler is an assay system, controlled by a Commodore PET computer, that measures the plutonium content in leached hulls at the fuel reprocessing plant in Dounreay, Scotland. The Shuffler contains a 252 Cf neutron source that is moved between storage and irradiation locations to obtain measurement data. A stepping motor control (SMC) module operates the Shuffler and accepts commands from the PET to move the source. This manual briefly describes the Shuffler and provides details on running and using the diagnostic software program. The communications protocol for message transmittal between the PET and SMC is defined and a detailed example of message sending is presented in an appendix

Void Fraction Instrument operation and maintenance manual

International Nuclear Information System (INIS)

Borgonovi, G.; Stokes, T.I.; Pearce, K.L.; Martin, J.D.; Gimera, M.; Graves, D.B.

1994-09-01

This Operations and Maintenance Manual (O ampersand MM) addresses riser installation, equipment and personnel hazards, operating instructions, calibration, maintenance, removal, and other pertinent information necessary to safely operate and store the Void Fraction Instrument. Final decontamination and decommissioning of the Void Fraction Instrument are not covered in this document

Davis PV plant operation and maintenance manual

Energy Technology Data Exchange (ETDEWEB)

NONE

1994-09-01

This operation and maintenance manual contains the information necessary to run the Photovoltaics for Utility Scale Applications (PVUSA) test facility in Davis, California. References to more specific information available in drawings, data sheets, files, or vendor manuals are included. The PVUSA is a national cooperative research and demonstration program formed in 1987 to assess the potential of utility scale photovoltaic systems.

Computerized operation manual (COM) of nuclear power plants

International Nuclear Information System (INIS)

Szegi, Z.

1985-01-01

This paper is to be presented at the International Seminar on Diagnoses of and Response to Abnormal Occurrences at Nuclear Power Plants organized by the International Atomic Energy Agency. The topic of presentation is the Computerized Operational Manual. This system supports the operator at disturbance situations by displaying quickly and unambiguously the operational instructions and the relevant information without mistakes. By the computerized manual the operator can determine the instruction-subsystem which reflects the real state of the power unit. From this point the system guides the operator on how to drive the unit to another determined state by providing the operational instructions at any time. A data bank is also included which contains information concerning rules restricting on maintenance and repair. The system will be realized at Paks NPP. (author)

Survey of protocols for the manual segmentation of the hippocampus: preparatory steps towards a joint EADC-ADNI harmonized protocol.

Science.gov (United States)

Boccardi, Marina; Ganzola, Rossana; Bocchetta, Martina; Pievani, Michela; Redolfi, Alberto; Bartzokis, George; Camicioli, Richard; Csernansky, John G; de Leon, Mony J; deToledo-Morrell, Leyla; Killiany, Ronald J; Lehéricy, Stéphane; Pantel, Johannes; Pruessner, Jens C; Soininen, H; Watson, Craig; Duchesne, Simon; Jack, Clifford R; Frisoni, Giovanni B

2011-01-01

Manual segmentation from magnetic resonance imaging (MR) is the gold standard for evaluating hippocampal atrophy in Alzheimer's disease (AD). Nonetheless, different segmentation protocols provide up to 2.5-fold volume differences. Here we surveyed the most frequently used segmentation protocols in the AD literature as a preliminary step for international harmonization. The anatomical landmarks (anteriormost and posteriormost slices, superior, inferior, medial, and lateral borders) were identified from 12 published protocols for hippocampal manual segmentation ([Abbreviation] first author, publication year: [B] Bartzokis, 1998; [C] Convit, 1997; [dTM] deToledo-Morrell, 2004; [H] Haller, 1997; [J] Jack, 1994; [K] Killiany, 1993; [L] Lehericy, 1994; [M] Malykhin, 2007; [Pa] Pantel, 2000; [Pr] Pruessner, 2000; [S] Soininen, 1994; [W] Watson, 1992). The hippocampi of one healthy control and one AD patient taken from the 1.5T MR ADNI database were segmented by a single rater according to each protocol. The accuracy of the protocols' interpretation and translation into practice was checked with lead authors of protocols through individual interactive web conferences. Semantically harmonized landmarks and differences were then extracted, regarding: (a) the posteriormost slice, protocol [B] being the most restrictive, and [H, M, Pa, Pr, S] the most inclusive; (b) inclusion [C, dTM, J, L, M, Pr, W] or exclusion [B, H, K, Pa, S] of alveus/fimbria; (c) separation from the parahippocampal gyrus, [C] being the most restrictive, [B, dTM, H, J, Pa, S] the most inclusive. There were no substantial differences in the definition of the anteriormost slice. This survey will allow us to operationalize differences among protocols into tracing units, measure their impact on the repeatability and diagnostic accuracy of manual hippocampal segmentation, and finally develop a harmonized protocol.

Spent nuclear fuel project cold vacuum drying facility operations manual

International Nuclear Information System (INIS)

IRWIN, J.J.

1999-01-01

This document provides the Operations Manual for the Cold Vacuum Drying Facility (CVDF). The Manual was developed in conjunction with HNF-SD-SNF-SAR-002, Safety Analysis Report for the Cold Vacuum Drying Facility, Phase 2, Supporting Installation of Processing Systems (Garvin 1998) and, the HNF-SD-SNF-DRD-002, 1997, Cold Vacuum Drying Facility Design Requirements, Rev. 3a. The Operations Manual contains general descriptions of all the process, safety and facility systems in the CVDF, a general CVD operations sequence, and has been developed for the SNFP Operations Organization and shall be updated, expanded, and revised in accordance with future design, construction and startup phases of the CVDF until the CVDF final ORR is approved

Spent Nuclear Fuel (SNF) Cold Vacuum Drying (CVD) Facility Operations Manual

Energy Technology Data Exchange (ETDEWEB)

IRWIN, J.J.

1999-07-02

This document provides the Operations Manual for the Cold Vacuum Drying Facility (CVDF). The Manual was developed in conjunction with HNF-553, Spent Nuclear Fuel Project Final Safety Analysis Report Annex B--Cold Vacuum Drying Facility. The HNF-SD-SNF-DRD-002, 1999, Cold Vacuum Drying Facility Design Requirements, Rev. 4, and the CVDF Final Design Report. The Operations Manual contains general descriptions of all the process, safety and facility systems in the CVDF, a general CVD operations sequence and references to the CVDF System Design Descriptions (SDDs). This manual has been developed for the SNFP Operations Organization and shall be updated, expanded, and revised in accordance with future design, construction and startup phases of the CVDF until the CVDF final ORR is approved.

User's manual (UM) for the enhanced logistics intratheater support tool (ELIST) software segment version 8.1.0.0 for solaris 7.; TOPICAL

International Nuclear Information System (INIS)

Dritz, K.

2002-01-01

This document is the User's Manual (UM) for the Enhanced Logistics Intratheater Support Tool (ELIST) Software Segment. It tells how to use the end-user and administrative features of the segment. The instructions in Sections 4.2.1, 5.3.1, and 5.3.2 for the end-user features (Run ELIST and Run ETEdit) only cover the launching of those features in the DII COE environment; full details on the operation of ELIST and ETEdit in any environment can be found in the documents listed in Section 2.1.3 and referenced elsewhere in this document. On the other hand, complete instructions for the administrative features (Add Map Data and Delete Map Data) are presented in Sections 4.2.2, 5.3.3, and 5.3.4 of this document

Quantitative right and left ventricular functional analysis during gated whole-chest MDCT: A feasibility study comparing automatic segmentation to semi-manual contouring

International Nuclear Information System (INIS)

Coche, Emmanuel; Walker, Matthew J.; Zech, Francis; Crombrugghe, Rodolphe de; Vlassenbroek, Alain

2010-01-01

Purpose: To evaluate the feasibility of an automatic, whole-heart segmentation algorithm for measuring global heart function from gated, whole-chest MDCT images. Material and methods: 15 patients with suspicion of PE underwent whole-chest contrast-enhanced MDCT with retrospective ECG synchronization. Two observers computed right and left ventricular functional indices using a semi-manual and an automatic whole-heart segmentation algorithm. The two techniques were compared using Bland-Altman analysis and paired Student's t-test. Measurement reproducibility was calculated using intraclass correlation coefficient. Results: Ventricular analysis with automatic segmentation was successful in 13/15 (86%) and in 15/15 (100%) patients for the right ventricle and left ventricle, respectively. Reproducibility of measurements for both ventricles was perfect (ICC: 1.00) and very good for automatic and semi-manual measurements, respectively. Ventricular volumes and functional indices except right ventricular ejection fraction obtained from the automatic method were significantly higher for the RV compared to the semi-manual methods. Conclusions: The automatic, whole-heart segmentation algorithm enabled highly reproducible global heart function to be rapidly obtained in patients undergoing gated whole-chest MDCT for assessment of acute chest pain with suspicion of pulmonary embolism.

US Fish and Wildlife Service lands biomonitoring operations manual

Energy Technology Data Exchange (ETDEWEB)

Rope, R.C.; Breckenridge, R.P.

1993-08-01

This is Volume 1 of an operations manual designed to facilitate the development of biomonitoring strategies for U.S. Fish and Wildlife Service Lands. It is one component of the U.S. Fish and Wildlife Service Lands Biomonitoring Operations Manual. The Volume contains the Introduction to the Manual, background information on monitoring, and procedures for developing a biomonitoring strategy for Service lands. The purpose of the Biomonitoring Operations Manual is to provide an approach to develop and implement biomonitoring activities to assess the status and trends of U.S. Fish and Wildlife Service trust resources. It also provides field sampline methods and documentation protocols for contaminant monitoring activities. The strategy described in the Manual has been designed as a stand alone process to characterize the presence of contaminants on lands managed by the Service. This process can be sued to develop a monitoring program for any tract of real estate with potential threats from on- or off-site contaminants. Because the process was designed to address concerns for Service lands that span the United States from Alaska to the Tropical Islands, it has a generic format that can be used in al types of ecosystems, however, significant site specific informtion is required to complete the Workbook and make the process work successfully.

Janus neodymium glass laser operations manual

International Nuclear Information System (INIS)

Auerbach, J.M.; Holmes, N.C.; Trainor, R.J.

1978-01-01

A manual, prepared to guide personnel in operating and maintaining the Janus glass laser system, is presented. System components are described in detail. Step-by-step procedures are presented for firing the laser and for performing routine maintenance and calibration procedures

EMSL Operations Manual

Energy Technology Data Exchange (ETDEWEB)

Foster, Nancy S.

2009-06-18

This manual is a general resource tool to assist EMSL users and Laboratory staff within EMSL locate official policy, practice and subject matter experts. It is not intended to replace or amend any formal Battelle policy or practice. Users of this manual should rely only on Battelle’s Standard Based Management System (SBMS) for official policy. No contractual commitment or right of any kind is created by this manual. Battelle management reserves the right to alter, change, or delete any information contained within this manual without prior notice.

EMSL Operations Manual

Energy Technology Data Exchange (ETDEWEB)

Foster, Nancy S.

2009-03-25

This manual is a general resource tool to assist EMSL users and Laboratory staff within EMSL locate official policy, practice and subject matter experts. It is not intended to replace or amend any formal Battelle policy or practice. Users of this manual should rely only on Battelle’s Standard Based Management System (SBMS) for official policy. No contractual commitment or right of any kind is created by this manual. Battelle management reserves the right to alter, change, or delete any information contained within this manual without prior notice.

Manual rotation to decrease operative delivery in posterior or transverse positions.

Science.gov (United States)

Le Ray, Camille; Deneux-Tharaux, Catherine; Khireddine, Imane; Dreyfus, Michel; Vardon, Delphine; Goffinet, François

2013-09-01

To assess the effect of a policy of manual rotation on the mode of delivery of fetuses in posterior or transverse positions at full dilatation. This was a prospective study to compare two policies of management for posterior and transverse positions in two different hospitals (Hospital 1: no manual rotation and Hospital 2: manual rotation). We used univariable and multivariable analyses to study the association between the management policy for posterior and transverse positions at full dilatation in these hospitals and maternal and neonatal outcomes. The principal end point was operative delivery (ie, cesarean or instrumental vaginal delivery). All factors associated with the risk of operative delivery in the univariable analysis (Pmanual rotation was independently associated with a reduction in operative deliveries. The rate of posterior or transverse positions at full dilatation was 15.9% (n=111) in Hospital 1 and 15.3% (n=220) in Hospital 2 (P=.75). Of the 172 attempts of manual rotation in Hospital 2, 155 (90.1%) were successful. The rate of operative delivery was significantly lower in Hospital 2, which performed manual rotations (23.2% compared with 38.7% in Hospital 1, adjusted odds ratio [OR] 0.52, 95% confidence interval [CI] 0.28-0.95). After multivariable analysis, manual rotation remained significantly associated with a reduction in the risk of operative delivery (adjusted OR 0.45, 95% CI 0.25-0.85). Five-minute Apgar score and arterial pH at birth were similar in the two hospitals. For fetuses in posterior or transverse positions at full dilatation, a strategy of manual rotation is associated with a reduction in the rate of operative delivery. III.

Simplified operation manual PA-720 particle counter

International Nuclear Information System (INIS)

Draper, V.F.

1980-01-01

The model PA-720 Automatic Particle Size Analyzer is a simple, relatively high speed device designed to provide accurate size distributions in both tabular and graphic forms. This model has two dynamic ranges; 50 to 2500 microns and 200 to 1600 microns. This is an abbreviated version of the manufacturer's operating manual. It provides all the necessary information for the novice and experienced user. For more detailed explanations and servicing procedures one should reference the full manual

The energy management manual for arena and rink operators

Energy Technology Data Exchange (ETDEWEB)

Raymer, M. [Saskatchewan Parks and Recreation Assoc., Regina, SK (Canada); White, T. [Office of Energy Conservation, Regina, SK (Canada); Kozoriz, D.F. [SaskPower, Regina, SK (Canada); Norman, D. [SaskPower, Saskatoon, SK (Canada)

2006-08-15

In an era when energy costs often rise faster than the community tax base, energy conservation plays a key role in ensuring that skating arenas are able to continue operating. This manual on energy management for arena and rink operators includes current technologies and practices that reduce operating costs. It is meant to help in the training and education of all facility operators. Since fossil fuels are the main source of electrical generation in Saskatchewan, reducing energy consumption directly reduces greenhouse gas emissions to the environment. This manual included a brief introduction to energy calculations for operators of rinks and arenas. The calculations can be performed for the heat loss that occurs in winter and the amount of heat input needed to maintain temperatures. It was recommended that the more difficult calculation of estimating the amount of cooling required for ice making should be done by qualified consultants. The 10 sections of the manual addressed the issues of: (1) electrical and natural gas rates, (2) meters and electrical inventory, (3) making a financial analysis, (4) the building envelope, (5) heating and ventilation, (6) refrigeration, (7) lighting, (8) heating effects of electrical equipment, (9) operation and maintenance, and, (10) project planning. The manual also presented methods to improve the power factor by adding relatively inexpensive components, such as capacitors, to lower electricity bills by as much as 20 per cent. A review of geo-exchange systems for rinks and arenas was included along with heat recovery from refrigeration systems and financial assistance for commercial, institutional and municipal buildings. refs., tabs., figs.

Delphi definition of the EADC-ADNI Harmonized Protocol for hippocampal segmentation on magnetic resonance

NARCIS (Netherlands)

Boccardi, M.; Bocchetta, M.; Apostolova, L.G.; Barnes, J.; Bartzokis, G.; Corbetta, G.; deCarli, C.; DeToledo-Morrell, L.; Firbank, M.; Ganzola, R.; Gerritsen, L.; Henneman, W.; Killiany, R.J.; Malykhin, N.; Pasqualetti, P.; Pruessner, J.C.; Redolfi, A.; Robitaille, N.; Soininen, H.; Tolomeo, D.; Wang, L.; Watson, C.; Wolf, H; Duvernoy, H.; Duchesne, S.; Jack, C.R.; Frisoni, G. B.

2015-01-01

Background: This study aimed to have international experts converge on a harmonized definition of whole hippocampus boundaries and segmentation procedures, to define standard operating procedures for magnetic resonance (MR)-based manual hippocampal segmentation. Methods: The panel received a

The design of operating procedures manuals for nuclear power plants

International Nuclear Information System (INIS)

Bohr, E.; Preuss, W.; Reinartz, G.; Thau, G.

1977-03-01

This report describes the findings of a research on the desirable design of operating procedures manuals for nuclear power plants. The work was supported by a grant of the Federal Department of the Interior. Information was acquired from different sources. Interviews and discussions on manual design were carried out with manual users in nuclear power plants. Moreover, tasks carried out using procedures were either observed or, alternatively, the manner of using procedures was elicited by interviews. In addition, manual writers, managers from manufacturers and utilities, nuclear experts, and individuals involved in manual specification activities were interviewed. A major source of information has been the pertinent scientific and technical findings scattered in the literature on topics such as instructional technology, engineering psychology, psycholinguistics, and typography. A comprehensive bibliography is included. General rules are established on designing instructional material for use on the job, aiming at increasing their legability, comprehensibility, and suitability to guide human performance. The application of these rules to the design of individual operating procedures is demonstrated. Recommendations are given on the design, layout, development and implementation of manuals. (orig.) [de

Spent Nuclear Fuel (SNF) Cold Vacuum Drying (CVD) Facility Operations Manual; FINAL

International Nuclear Information System (INIS)

IRWIN, J.J.

1999-01-01

This document provides the Operations Manual for the Cold Vacuum Drying Facility (CVDF). The Manual was developed in conjunction with HNF-553, Spent Nuclear Fuel Project Final Safety Analysis Report Annex B-Cold Vacuum Drying Facility. The HNF-SD-SNF-DRD-002, 1999, Cold Vacuum Drying Facility Design Requirements, Rev. 4, and the CVDF Final Design Report. The Operations Manual contains general descriptions of all the process, safety and facility systems in the CVDF, a general CVD operations sequence and references to the CVDF System Design Descriptions (SDDs). This manual has been developed for the SNFP Operations Organization and shall be updated, expanded, and revised in accordance with future design, construction and startup phases of the CVDF until the CVDF final ORR is approved

76 FR 63628 - Preliminary Damage Assessment for Individual Assistance Operations Manual (9327.2-PR)

Science.gov (United States)

2011-10-13

...] Preliminary Damage Assessment for Individual Assistance Operations Manual (9327.2-PR) AGENCY: Federal... Individual Assistance Operations Manual (9327.2-PR). DATES: Comments must be received by November 14, 2011... of the draft Preliminary Damage Assessment for Individual Assistance Operations Manual (9327.2-PR) on...

Development of a health and safety manual for emergency response operations

International Nuclear Information System (INIS)

Riland, C.A.; Junio, S.S.

2000-01-01

The Federal Radiological Monitoring and Assessment Center (FRMAC) Health and Safety Manual, which has been under development by a multi-agency group, is nearing completion and publication. The manual applies to offsite monitoring during a radiological accident or incident. Though written for multi-agency offsite monitoring activities (FRMAC), the manual is generic in nature and should be readily adaptable for other emergency response operations. Health and safety issues for emergency response situations often differ from those of normal operations. Examples of these differences and methodologies to address these issues are discussed. Challenges in manual development, including lack of regulatory and guidance documentation, are also discussed. One overriding principle in the Health and Safety Manual development is the overall reduction of risk, not just dose. The manual is broken into several chapters, which include Overview of Responsibities, Health Physics, Industrial Hygiene and Safey, Medical, and Environmental Compliance and Records. Included is a series of appendices, which presents additional information on forms and plans for default scenarios

Operation and Maintenance Manual for the Central Facilities Area Sewage Treatment Plant

Energy Technology Data Exchange (ETDEWEB)

Norm Stanley

2011-02-01

This Operation and Maintenance Manual lists operator and management responsibilities, permit standards, general operating procedures, maintenance requirements and monitoring methods for the Sewage Treatment Plant at the Central Facilities Area at the Idaho National Laboratory. The manual is required by the Municipal Wastewater Reuse Permit (LA-000141-03) the sewage treatment plant.

An annotated outline for a traffic management center operations manual

Science.gov (United States)

2000-10-01

This draft Traffic Management Center (TMC) and Operations manual outline is meant to serve as a model "checklist" for the development of similar manuals used in deployed environments. The purpose of this outline is to provide a reference for agencies...

Manual for the operation of research reactors

International Nuclear Information System (INIS)

1965-01-01

The great majority of the research reactors in newly established centres are light-water cooled and are often also light-water moderated. Consequently, the IAEA has decided to publish in its Technical Reports Series a manual dealing with the technical and practical problems associated with the safe and efficient operation of this type of reactor. Even though this manual is limited to light-water reactors in its direct application and presents the practices and experience at one specific reactor centre, it may also be useful for other reactor types because of the general relevance of the problems discussed and the long experience upon which it is based. It has, naturally, no regulatory character but it is hoped that it will be found helpful by staff occupied in all phases of the practical operation of research reactors, and also by those responsible for planning their experimental use. 23 refs, tabs

Surface Moisture Measurement System Operation and Maintenance Manual

International Nuclear Information System (INIS)

Ritter, G.A.; Pearce, K.L.; Stokes, T.L.

1995-12-01

This operations and maintenance manual addresses deployment, equipment and field hazards, operating instructions, calibration verification, removal, maintenance, and other pertinent information necessary to safely operate and store the Surface Moisture Measurement System (SMMS) and Liquid Observation Well Moisture Measurement System (LOWMMS). These systems were developed primarily in support of Tank Waste Remediation System (TWRS) Safety Programs for moisture measurement in organic and ferrocyanide watch list tanks

FRMAC Operations Manual

Energy Technology Data Exchange (ETDEWEB)

Frandsen, K.

2010-05-01

In the event of a major radiological incident, the Federal Radiological Monitoring and Assessment Center (FRMAC) will coordinate the federal agencies that have various statutory responsibilities. The FRMAC is responsible for coordinating all environmental radiological monitoring, sampling, and assessment activities for the response. This manual describes the FRMAC’s response activities in a radiological incident. It also outlines how FRMAC fits in the National Incident Management System (NIMS) under the National Response Framework (NRF) and describes the federal assets and subsequent operational activities which provide federal radiological monitoring and assessment of the affected areas. In the event of a potential or existing major radiological incident, the U.S. Department of Energy (DOE), National Nuclear Security Administration Nevada Site Office (NNSA/NSO) is responsible for establishing and managing the FRMAC during the initial phases.

Data collection system. Volume 1, Overview and operators manual; Volume 2, Maintenance manual; Appendices

Energy Technology Data Exchange (ETDEWEB)

Caudell, R.B.; Bauder, M.E.; Boyer, W.B.; French, R.E.; Isidoro, R.J.; Kaestner, P.C.; Perkins, W.G.

1993-09-01

Sandia National Laboratories (SNL) Instrumentation Development Department was tasked by the Defense Nuclear Agency (DNA) to record data on Tektronix RTD720 Digitizers on the HUNTERS TROPHY field test conducted at the Nevada Test Site (NTS) on September 18, 1992. This report contains a overview and description of the computer hardware and software that was used to acquire, reduce, and display the data. The document is divided into two volumes: an overview and operators manual (Volume 1) and a maintenance manual (Volume 2).

The IXV Ground Segment design, implementation and operations

Science.gov (United States)

Martucci di Scarfizzi, Giovanni; Bellomo, Alessandro; Musso, Ivano; Bussi, Diego; Rabaioli, Massimo; Santoro, Gianfranco; Billig, Gerhard; Gallego Sanz, José María

2016-07-01

The Intermediate eXperimental Vehicle (IXV) is an ESA re-entry demonstrator that performed, on the 11th February of 2015, a successful re-entry demonstration mission. The project objectives were the design, development, manufacturing and on ground and in flight verification of an autonomous European lifting and aerodynamically controlled re-entry system. For the IXV mission a dedicated Ground Segment was provided. The main subsystems of the IXV Ground Segment were: IXV Mission Control Center (MCC), from where monitoring of the vehicle was performed, as well as support during pre-launch and recovery phases; IXV Ground Stations, used to cover IXV mission by receiving spacecraft telemetry and forwarding it toward the MCC; the IXV Communication Network, deployed to support the operations of the IXV mission by interconnecting all remote sites with MCC, supporting data, voice and video exchange. This paper describes the concept, architecture, development, implementation and operations of the ESA Intermediate Experimental Vehicle (IXV) Ground Segment and outlines the main operations and lessons learned during the preparation and successful execution of the IXV Mission.

Time warp operating system version 2.7 internals manual

Science.gov (United States)

1992-01-01

The Time Warp Operating System (TWOS) is an implementation of the Time Warp synchronization method proposed by David Jefferson. In addition, it serves as an actual platform for running discrete event simulations. The code comprising TWOS can be divided into several different sections. TWOS typically relies on an existing operating system to furnish some very basic services. This existing operating system is referred to as the Base OS. The existing operating system varies depending on the hardware TWOS is running on. It is Unix on the Sun workstations, Chrysalis or Mach on the Butterfly, and Mercury on the Mark 3 Hypercube. The base OS could be an entirely new operating system, written to meet the special needs of TWOS, but, to this point, existing systems have been used instead. The base OS's used for TWOS on various platforms are not discussed in detail in this manual, as they are well covered in their own manuals. Appendix G discusses the interface between one such OS, Mach, and TWOS.

Spent Nuclear Fuel (SNF) Project Cold Vacuum Drying (CVD) Facility Operations Manual

Energy Technology Data Exchange (ETDEWEB)

IRWIN, J.J.

2000-02-03

This document provides the Operations Manual for the Cold Vacuum Drying Facility (CVDF). The Manual was developed in conjunction with HNF-SD-SNF-SAR-002, Safety Analysis Report for the Cold Vacuum Drying Facility, Phase 2, Supporting Installation of the Processing Systems (Garvin 1998) and, the HNF-SD-SNF-DRD-002, 1997, Cold Vacuum Drying Facility Design Requirements, Rev. 3a. The Operations Manual contains general descriptions of all the process, safety and facility systems in the CVDF, a general CVD operations sequence, and has been developed for the spent nuclear fuel project (SNFP) Operations Organization and shall be updated, expanded, and revised in accordance with future design, construction and startup phases of the CVDF until the CVDF final ORR is approved.

Spent Nuclear Fuel (SNF) Project Cold Vacuum Drying (CVD) Facility Operations Manual

International Nuclear Information System (INIS)

IRWIN, J.J.

2000-01-01

This document provides the Operations Manual for the Cold Vacuum Drying Facility (CVDF). The Manual was developed in conjunction with HNF-SD-SNF-SAR-002, Safety Analysis Report for the Cold Vacuum Drying Facility, Phase 2, Supporting Installation of the Processing Systems (Garvin 1998) and, the HNF-SD-SNF-DRD-002, 1997, Cold Vacuum Drying Facility Design Requirements, Rev. 3a. The Operations Manual contains general descriptions of all the process, safety and facility systems in the CVDF, a general CVD operations sequence, and has been developed for the spent nuclear fuel project (SNFP) Operations Organization and shall be updated, expanded, and revised in accordance with future design, construction and startup phases of the CVDF until the CVDF final ORR is approved

A Manually Operated Cassava Grating Machine | Odigboh | Nigerian ...

African Journals Online (AJOL)

The design and development of a manually operated cassava grating machine prototype are presented. The prototype grater is shown to be easy to operate at 30 - 45 rpm to give a product whose quality is as good as that from motorized graters at a throughput of 125 - 185 kg/h. The prototype grater is a powerful alternative ...

Operator's manual actions in case of fire; Acciones manuales del operador en caso de incendio

Energy Technology Data Exchange (ETDEWEB)

Saez de Tejada Madina, P.; Perez Lobo, E. M.; Velasco Ramirez, R.; Velasco Ramirez, R.; Fernandez Ramos, P.

2012-07-01

Vandellos II, following the guidelines GS 01.19 of CSN and RG 1.189 rev. 2, has identified the need to consider a number of local manual actions to be performed by the staff of shift operation and need to be validated according NUREG 1852. The local manual actions include corrective and preventive actions, such as local start and shooting of bombs, checking positions ... According NUREG-1852 these actions must be validated with conditions as similar as possible to those expected, in conjunction with the operating of Vandellos II.

Quality management for nuclear power plant operation: A manual

International Nuclear Information System (INIS)

1990-01-01

The experience from well operated nuclear power plants shows that achievement of safe, reliable and economic performance is closely related to a strong commitment and involvement by the management personnel. A system of controls is necessary to ensure that satisfactory quality in operation is achieved and maintained over the long term. The key to achieving and assuring quality lies in the ability of management to define performance objectives and to ensure that significant safety and reliability problems are prevented or detected early and resolved. This Manual has been developed by the IAEA to assist plant managers in fulfilling their responsibility with regard to the control and direction of quality and of quality assurance activities in nuclear power plant operation. It emphasizes quality objectives for nuclear power plant operation and indicates the way in which a quality system based on quality assurance principles as established in the IAEA NUSS documents can be used by managers to accomplish these objectives. Since the Manual is mainly directed at management personnel, it is presented in the form of short highlighted practices complemented by typical examples of forms and procedures. Since not all the activities under the heading of quality in operation could be covered in a single document, the activities selected for this Manual comprise those where it was felt that practical advice is generally needed. A pragmatic document useful for direct application by plant managers was the envisaged objective

A Manual of Simplified Laboratory Methods for Operators of Wastewater Treatment Facilities.

Science.gov (United States)

Westerhold, Arnold F., Ed.; Bennett, Ernest C., Ed.

This manual is designed to provide the small wastewater treatment plant operator, as well as the new or inexperienced operator, with simplified methods for laboratory analysis of water and wastewater. It is emphasized that this manual is not a replacement for standard methods but a guide for plants with insufficient equipment to perform analyses…

33 CFR 154.310 - Operations manual: Contents.

Science.gov (United States)

2010-07-01

..., maps, drawings, aerial photographs or diagrams, showing the boundaries of the facility subject to Coast... products and the location in the Operations Manual where a chart or list of symbols utilized is located and... vapor collection system at the facility which includes: (1) A line diagram or simplified piping and...

Quantification of Right and Left Ventricular Function in Cardiac MR Imaging: Comparison of Semiautomatic and Manual Segmentation Algorithms

Directory of Open Access Journals (Sweden)

Jose Martin Carreira

2013-04-01

Full Text Available The purpose of this study was to evaluate the performance of a semiautomatic segmentation method for the anatomical and functional assessment of both ventricles from cardiac cine magnetic resonance (MR examinations, reducing user interaction to a “mouse-click”. Fifty-two patients with cardiovascular diseases were examined using a 1.5-T MR imaging unit. Several parameters of both ventricles, such as end-diastolic volume (EDV, end-systolic volume (ESV and ejection fraction (EF, were quantified by an experienced operator using the conventional method based on manually-defined contours, as the standard of reference; and a novel semiautomatic segmentation method based on edge detection, iterative thresholding and region growing techniques, for evaluation purposes. No statistically significant differences were found between the two measurement values obtained for each parameter (p > 0.05. Correlation to estimate right ventricular function was good (r > 0.8 and turned out to be excellent (r > 0.9 for the left ventricle (LV. Bland-Altman plots revealed acceptable limits of agreement between the two methods (95%. Our study findings indicate that the proposed technique allows a fast and accurate assessment of both ventricles. However, further improvements are needed to equal results achieved for the right ventricle (RV using the conventional methodology.

Automatic segmentation of the left ventricle in a cardiac MR short axis image using blind morphological operation

Science.gov (United States)

Irshad, Mehreen; Muhammad, Nazeer; Sharif, Muhammad; Yasmeen, Mussarat

2018-04-01

Conventionally, cardiac MR image analysis is done manually. Automatic examination for analyzing images can replace the monotonous tasks of massive amounts of data to analyze the global and regional functions of the cardiac left ventricle (LV). This task is performed using MR images to calculate the analytic cardiac parameter like end-systolic volume, end-diastolic volume, ejection fraction, and myocardial mass, respectively. These analytic parameters depend upon genuine delineation of epicardial, endocardial, papillary muscle, and trabeculations contours. In this paper, we propose an automatic segmentation method using the sum of absolute differences technique to localize the left ventricle. Blind morphological operations are proposed to segment and detect the LV contours of the epicardium and endocardium, automatically. We test the benchmark Sunny Brook dataset for evaluation of the proposed work. Contours of epicardium and endocardium are compared quantitatively to determine contour's accuracy and observe high matching values. Similarity or overlapping of an automatic examination to the given ground truth analysis by an expert are observed with high accuracy as with an index value of 91.30% . The proposed method for automatic segmentation gives better performance relative to existing techniques in terms of accuracy.

FB-line neutron multiplicity counter operation manual

International Nuclear Information System (INIS)

Langner, D.G.; Sweet, M.R.; Salazar, S.D.; Kroncke, K.E.

1998-01-01

This manual describes the design features, performance, and operating characteristics for the FB-Line Neutron Multiplicity Counter (FBLNMC). The FBLNMC counts neutron multiplicities to quantitatively assay plutonium in many forms, including impure scrap and waste. Monte Carlo neutronic calculations were used to design the high-efficiency (57%) detector that has 113 3 H tubes in a high-density polyethylene body. The new derandomizer circuit is included in the design to reduce deadtime. The FBLNMC can be applied to plutonium masses in the range from a few tens of grams to 5 kg; both conventional coincidence counting and multiplicity counting can be used as appropriate. This manual gives the performance data and preliminary calibration parameters for the FBLNMC

Manual on environmental monitoring in normal operation

International Nuclear Information System (INIS)

1966-01-01

Many establishments handling radioactive materials produce, and to some extent also discharge, radioactive waste as part of their normal operation. The radiation doses to which members of the public may be exposed during such operation must remain below the stipulated level. The purpose of this manual is to provide technical guidance for setting up programmes of routine environmental monitoring in the vicinity of nuclear establishment. The annex gives five examples of routine environmental monitoring programmes currently in use: these have been indexed separately.

Operator's Manual, Boiler Room Operations and Maintenance. Supplement A, Air Pollution Training Institute Self-Instructional Course SI-466.

Science.gov (United States)

Environmental Protection Agency, Research Triangle Park, NC. Air Pollution Training Inst.

This Operator's Manual is a supplement to a self-instructional course prepared for the United States Environmental Protection Agency. This publication is the Boiler Room Handbook for operating and maintaining the boiler and the boiler room. As the student completes this handbook, he is putting together a manual for running his own boiler. The…

Rhythm-based segmentation of Popular Chinese Music

DEFF Research Database (Denmark)

Jensen, Karl Kristoffer

2005-01-01

We present a new method to segment popular music based on rhythm. By computing a shortest path based on the self-similarity matrix calculated from a model of rhythm, segmenting boundaries are found along the di- agonal of the matrix. The cost of a new segment is opti- mized by matching manual...... and automatic segment boundaries. We compile a small song database of 21 randomly selected popular Chinese songs which come from Chinese Mainland, Taiwan and Hong Kong. The segmenting results on the small corpus show that 78% manual segmentation points are detected and 74% auto- matic segmentation points...

33 CFR 157.156 - COW operations: Meeting manual requirements.

Science.gov (United States)

2010-07-01

... 33 Navigation and Navigable Waters 2 2010-07-01 2010-07-01 false COW operations: Meeting manual... CARRYING OIL IN BULK Crude Oil Washing (COW) System on Tank Vessels Cow Operations § 157.156 COW operations... COW system under §§ 157.10(e), 157.10a(a)(2), or 157.10c(b)(2) that has the Crude Oil Washing...

Operation manual for the INEL on-line mass-separator facility

International Nuclear Information System (INIS)

Anderl, R.A.

1984-06-01

This report is an operation manual for an on-line mass-separator facility which is located in Building 661 at the Test Reactor Area of the Idaho National Engineering Laboratory. The facility provides mass-separated sources of short-lived fission-product radionuclides whose decay properties can be studied using a variety of nuclear spectroscopic techniques. This facility is unique in that it utilizes the gas-jet technique to transport fission products from a 252 Cf source located in a hot cell to the ion source of the mass separator. This document includes the following: (a) a detailed description of the facility, (b) identification of equipment hazards and safety controls, (c) detailed operating procedures for startup, continuous operation and shutdown, (d) operating procedures for the californium hot cell, and (e) an operator's manual for the automated moving tape collector/data acquisition system. 7 references, 16 figures, 8 tables

Fully convolutional networks (FCNs)-based segmentation method for colorectal tumors on T2-weighted magnetic resonance images.

Science.gov (United States)

Jian, Junming; Xiong, Fei; Xia, Wei; Zhang, Rui; Gu, Jinhui; Wu, Xiaodong; Meng, Xiaochun; Gao, Xin

2018-06-01

Segmentation of colorectal tumors is the basis of preoperative prediction, staging, and therapeutic response evaluation. Due to the blurred boundary between lesions and normal colorectal tissue, it is hard to realize accurate segmentation. Routinely manual or semi-manual segmentation methods are extremely tedious, time-consuming, and highly operator-dependent. In the framework of FCNs, a segmentation method for colorectal tumor was presented. Normalization was applied to reduce the differences among images. Borrowing from transfer learning, VGG-16 was employed to extract features from normalized images. We conducted five side-output blocks from the last convolutional layer of each block of VGG-16 along the network, these side-output blocks can deep dive multiscale features, and produced corresponding predictions. Finally, all of the predictions from side-output blocks were fused to determine the final boundaries of the tumors. A quantitative comparison of 2772 colorectal tumor manual segmentation results from T2-weighted magnetic resonance images shows that the average Dice similarity coefficient, positive predictive value, specificity, sensitivity, Hammoude distance, and Hausdorff distance were 83.56, 82.67, 96.75, 87.85%, 0.2694, and 8.20, respectively. The proposed method is superior to U-net in colorectal tumor segmentation (P colorectal tumor segmentation (P > 0.05). The results indicate that the introduction of FCNs contributed to accurate segmentation of colorectal tumors. This method has the potential to replace the present time-consuming and nonreproducible manual segmentation method.

Integration of a browser based operator manual in the system environment of a process computer system

International Nuclear Information System (INIS)

Weber, Andreas; Erfle, Robert; Feinkohl, Dirk

2012-01-01

The integration of a browser based operator manual in the system environment of a process computer system is an optimization of the operating procedure in the control room and a safety enhancement due to faster and error-free access to the manual contents. Several requirements by the authorities have to be fulfilled: the operating manual has to be available as hard copy, the format has to be true to original, protection against manipulation has to be provided, the manual content of the browser-based version and the hard copy have to identical, and the display presentation has to be consistent with ergonomic principals. The integration of the on-line manual in the surveillance process computer system provides the operator with the relevant comments to the surveillance signal. The described integration of the on-line manual is an optimization of the operator's everyday job with respect to ergonomics and safety (human performance).

A quantitative analysis of two-dimensional manually segmented transrectal ultrasound axial images in planning high dose rate brachytherapy for prostate cancer

Directory of Open Access Journals (Sweden)

Dabić-Stanković Kata

2017-01-01

Full Text Available Background/Aim. Prostate delineation, pre-planning and catheter implantation procedures, in high-dose rate brachytherapy (HDR-BT, are commonly based on the prostate manually segmented transrectal ultrasound (TRUS images. The aim of this study was to quantitatively analyze the consistency of prostate capsule delineation, done by a single therapist, prior to each HDR-BT fraction and the changes in the shape of the prostate capsule during HDR-BT, using two dimensional (2D TRUS axial image. Methods. A group of 16 patients were treated at the Medical System Belgrade Brachytherapy Department with definitive HDRBT. The total applied median dose of 52 Gy was divided into four individual fractions, each fraction being delivered 2– 3 weeks apart. Real time prostate axial visualization and the manual segmentation prior to each fraction were performed using B-K Medical ultrasound. Quantitative analyses, analysis of an area and shape were applied on 2D-TRUS axial images of the prostate. Area analyses were used to calculate the average value of the cross-sectional area of the prostate image. The parameters of the prostate shape, the fractal dimension and the circularity ratio of the prostate capsule contour were estimated at the maximum axial cross section of the prostate image. Results. The sample group consisted of four phases, each phase being performed prior to the first, second, third and fourth HDR-BT fraction, respectively. Statistical analysis showed that during HDR-BT fractions there were no significant differences in the average value of area, as well as in the maximum shape of prostate capsule. Conclusions. Quantitative analysis of TRUS axial prostate segmented images shows a successful capsule delineation in the series of manually segmented TRUS images, and the prostate maximum shape remaining unchanged during HDR-BT fractions.

The EADC-ADNI Harmonized Protocol for manual hippocampal segmentation on magnetic resonance: Evidence of validity

Science.gov (United States)

Frisoni, Giovanni B.; Jack, Clifford R.; Bocchetta, Martina; Bauer, Corinna; Frederiksen, Kristian S.; Liu, Yawu; Preboske, Gregory; Swihart, Tim; Blair, Melanie; Cavedo, Enrica; Grothe, Michel J.; Lanfredi, Mariangela; Martinez, Oliver; Nishikawa, Masami; Portegies, Marileen; Stoub, Travis; Ward, Chadwich; Apostolova, Liana G.; Ganzola, Rossana; Wolf, Dominik; Barkhof, Frederik; Bartzokis, George; DeCarli, Charles; Csernansky, John G.; deToledo-Morrell, Leyla; Geerlings, Mirjam I.; Kaye, Jeffrey; Killiany, Ronald J.; Lehéricy, Stephane; Matsuda, Hiroshi; O'Brien, John; Silbert, Lisa C.; Scheltens, Philip; Soininen, Hilkka; Teipel, Stefan; Waldemar, Gunhild; Fellgiebel, Andreas; Barnes, Josephine; Firbank, Michael; Gerritsen, Lotte; Henneman, Wouter; Malykhin, Nikolai; Pruessner, Jens C.; Wang, Lei; Watson, Craig; Wolf, Henrike; deLeon, Mony; Pantel, Johannes; Ferrari, Clarissa; Bosco, Paolo; Pasqualetti, Patrizio; Duchesne, Simon; Duvernoy, Henri; Boccardi, Marina

2015-01-01

Background An international Delphi panel has defined a harmonized protocol (HarP) for the manual segmentation of the hippocampus on MR. The aim of this study is to study the concurrent validity of the HarP toward local protocols, and its major sources of variance. Methods Fourteen tracers segmented 10 Alzheimer's Disease Neuroimaging Initiative (ADNI) cases scanned at 1.5 T and 3T following local protocols, qualified for segmentation based on the HarP through a standard web-platform and resegmented following the HarP. The five most accurate tracers followed the HarP to segment 15 ADNI cases acquired at three time points on both 1.5 T and 3T. Results The agreement among tracers was relatively low with the local protocols (absolute left/right ICC 0.44/0.43) and much higher with the HarP (absolute left/right ICC 0.88/0.89). On the larger set of 15 cases, the HarP agreement within (left/right ICC range: 0.94/0.95 to 0.99/0.99) and among tracers (left/right ICC range: 0.89/0.90) was very high. The volume variance due to different tracers was 0.9% of the total, comparing favorably to variance due to scanner manufacturer (1.2), atrophy rates (3.5), hemispheric asymmetry (3.7), field strength (4.4), and significantly smaller than the variance due to atrophy (33.5%, P < .001), and physiological variability (49.2%, P < .001). Conclusions The HarP has high measurement stability compared with local segmentation protocols, and good reproducibility within and among human tracers. Hippocampi segmented with the HarP can be used as a reference for the qualification of human tracers and automated segmentation algorithms. PMID:25267715

Regional Test Center Operations Manual

Energy Technology Data Exchange (ETDEWEB)

Stein, Joshua [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Burnham, Laurie [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Jones, Christian Birk [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2017-07-01

The U.S. DOE Regional Test Center for Solar Technologies program was established to validate photovoltaic (PV) technologies installed in a range of different climates. The program is funded by the Energy Department's SunShot Initiative. The initiative seeks to make solar energy cost competitive with other forms of electricity by the end of the decade. Sandia National Laboratory currently manages four different sites across the country. The National Renewable Energy Laboratory manages a fifth site in Colorado. The entire PV portfolio currently includes 20 industry partners and almost 500 kW of installed systems. The program follows a defined process that outlines tasks, milestones, agreements, and deliverables. The process is broken out into four main parts: 1) planning and design, 2) installation, 3) operations, and 4) decommissioning. This operations manual defines the various elements of each part.

49 CFR 192.605 - Procedural manual for operations, maintenance, and emergencies.

Science.gov (United States)

2010-10-01

... operation of pressure-limiting and control devices. (6) Maintaining compressor stations, including... operations of a pipeline system commence. Appropriate parts of the manual must be kept at locations where..., operating and shutting down gas compressor units. (8) Periodically reviewing the work done by operator...

49 CFR 236.919 - Operations and Maintenance Manual.

Science.gov (United States)

2010-10-01

..., INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Standards for Processor-Based Signal and Train Control Systems § 236.919 Operations and Maintenance Manual. (a... identify all software versions, revisions, and revision dates. Plans must be legible and correct. (c...

49 CFR 236.1039 - Operations and Maintenance Manual.

Science.gov (United States)

2010-10-01

..., INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Positive Train Control Systems § 236.1039 Operations and Maintenance Manual. (a) The railroad shall catalog and... software versions, revisions, and revision dates. Plans must be legible and correct. (c) Hardware, software...

User's manual (UM) for the enhanced logistics intratheater support tool (ELIST) database utility segment version 8.1.0.0 for solaris 7.; TOPICAL

International Nuclear Information System (INIS)

Dritz, K.

2002-01-01

This document is the User's Manual (UM) for the Enhanced Logistics Intratheater Support Tool (ELIST) Database Utility Segment. It tells how to use its features to administer ELIST database user accounts

Transportable Xenon Laboratory (TXL-1) Operations Manual

Energy Technology Data Exchange (ETDEWEB)

Thompson, Robert C.; Stewart, Timothy L.; Willett, Jesse A.; Woods, Vincent T.

2011-03-07

The Transportable Xenon Laboratory Operations Manual is a guide to set up and shut down TXL, a fully contained laboratory made up of instruments to identify and measure concentrations of the radioactive isotopes of xenon by taking air samples and analyzing them. The TXL is housed in a standard-sized shipping container. TXL can be shipped to and function in any country in the world.

Fast prostate segmentation for brachytherapy based on joint fusion of images and labels

Science.gov (United States)

Nouranian, Saman; Ramezani, Mahdi; Mahdavi, S. Sara; Spadinger, Ingrid; Morris, William J.; Salcudean, Septimiu E.; Abolmaesumi, Purang

2014-03-01

Brachytherapy as one of the treatment methods for prostate cancer takes place by implantation of radioactive seeds inside the gland. The standard of care for this treatment procedure is to acquire transrectal ultrasound images of the prostate which are segmented in order to plan the appropriate seed placement. The segmentation process is usually performed either manually or semi-automatically and is associated with subjective errors because the prostate visibility is limited in ultrasound images. The current segmentation process also limits the possibility of intra-operative delineation of the prostate to perform real-time dosimetry. In this paper, we propose a computationally inexpensive and fully automatic segmentation approach that takes advantage of previously segmented images to form a joint space of images and their segmentations. We utilize joint Independent Component Analysis method to generate a model which is further employed to produce a probability map of the target segmentation. We evaluate this approach on the transrectal ultrasound volume images of 60 patients using a leave-one-out cross-validation approach. The results are compared with the manually segmented prostate contours that were used by clinicians to plan brachytherapy procedures. We show that the proposed approach is fast with comparable accuracy and precision to those found in previous studies on TRUS segmentation.

A protocol for manual segmentation of medial temporal lobe subregions in 7 Tesla MRI

Directory of Open Access Journals (Sweden)

D. Berron

2017-01-01

Full Text Available Recent advances in MRI and increasing knowledge on the characterization and anatomical variability of medial temporal lobe (MTL anatomy have paved the way for more specific subdivisions of the MTL in humans. In addition, recent studies suggest that early changes in many neurodegenerative and neuropsychiatric diseases are better detected in smaller subregions of the MTL rather than with whole structure analyses. Here, we developed a new protocol using 7 Tesla (T MRI incorporating novel anatomical findings for the manual segmentation of entorhinal cortex (ErC, perirhinal cortex (PrC; divided into area 35 and 36, parahippocampal cortex (PhC, and hippocampus; which includes the subfields subiculum (Sub, CA1, CA2, as well as CA3 and dentate gyrus (DG which are separated by the endfolial pathway covering most of the long axis of the hippocampus. We provide detailed instructions alongside slice-by-slice segmentations to ease learning for the untrained but also more experienced raters. Twenty-two subjects were scanned (19–32 yrs, mean age = 26 years, 12 females with a turbo spin echo (TSE T2-weighted MRI sequence with high-resolution oblique coronal slices oriented orthogonal to the long axis of the hippocampus (in-plane resolution 0.44×0.44 mm2 and 1.0 mm slice thickness. The scans were manually delineated by two experienced raters, to assess intra- and inter-rater reliability. The Dice Similarity Index (DSI was above 0.78 for all regions and the Intraclass Correlation Coefficients (ICC were between 0.76 to 0.99 both for intra- and inter-rater reliability. In conclusion, this study presents a fine-grained and comprehensive segmentation protocol for MTL structures at 7 T MRI that closely follows recent knowledge from anatomical studies. More specific subdivisions (e.g. area 35 and 36 in PrC, and the separation of DG and CA3 may pave the way for more precise delineations thereby enabling the detection of early volumetric changes in dementia and

Semi-automatic watershed medical image segmentation methods for customized cancer radiation treatment planning simulation

International Nuclear Information System (INIS)

Kum Oyeon; Kim Hye Kyung; Max, N.

2007-01-01

A cancer radiation treatment planning simulation requires image segmentation to define the gross tumor volume, clinical target volume, and planning target volume. Manual segmentation, which is usual in clinical settings, depends on the operator's experience and may, in addition, change for every trial by the same operator. To overcome this difficulty, we developed semi-automatic watershed medical image segmentation tools using both the top-down watershed algorithm in the insight segmentation and registration toolkit (ITK) and Vincent-Soille's bottom-up watershed algorithm with region merging. We applied our algorithms to segment two- and three-dimensional head phantom CT data and to find pixel (or voxel) numbers for each segmented area, which are needed for radiation treatment optimization. A semi-automatic method is useful to avoid errors incurred by both human and machine sources, and provide clear and visible information for pedagogical purpose. (orig.)

Effects of operator time pressure and noise on manual ultrasonic testing

International Nuclear Information System (INIS)

Enkvist, J.; Edland, A.; Svenson, O.

2002-01-01

In earlier studies of manual ultrasonic testing, great variations have been found in operator performance, often attributed to operator fatigue. However, no conclusive findings have been reported. In the present study, twenty operators performed manual ultrasonic inspections of six test-pieces with manufactured flaws. The operators performed the inspections under stress (high arousal - time pressure and noise) and no-stress conditions; one condition the first day and the other the second and last day. According to the Yerkes-Dodson Law there is an optimal arousal level where performance is highest. It was hypothesised that the stress condition led to a level of arousal so high that it would affect the results negatively. However, contrary to the hypotheses it was found that the manipulation increased operator performance. Operators with the stress condition day 1 performed better than the other operators (under the no-stress condition). This was interpreted as the 'stress first' (group 1) operators had established efficient performance patterns the first day - affecting also the second day. Operators beginning with stress condition also tended to be more motivated. It was concluded that operator performance is affected by arousal. (author)

System administrator's manual (SAM) for the enhanced logistics intratheater support tool (ELIST) database segment version 8.1.0.0 for solaris 7.; TOPICAL

International Nuclear Information System (INIS)

Dritz, K.

2002-01-01

This document is the System Administrator's Manual (SAM) for the Enhanced Logistics Intratheater Support Tool (ELIST) Database Segment. It covers errors that can arise during the segment's installation and deinstallation, and it outlines appropriate recovery actions. It also tells how to extend the database storage available to Oracle if a datastore becomes filled during the use of ELIST. The latter subject builds on some of the actions that must be performed when installing this segment, as documented in the Installation Procedures (IP) for the Enhanced Logistics Intratheater Support Tool (ELIST) Global Data Segment, Database Instance Segment, Database Fill Segment, Database Segment, Database Utility Segment, Software Segment, and Reference Data Segment (referred to in portions of this document as the ELIST IP). The information in this document is expected to be of use only rarely. Other than errors arising from the failure to follow instructions, difficulties are not expected to be encountered during the installation or deinstallation of the segment. The need to extend database storage likewise typically arises infrequently. Most administrators will only need to be aware of the help that is provided in this document and will probably not actually need to read and make use of it

Robust semi-automatic segmentation of pulmonary subsolid nodules in chest computed tomography scans

International Nuclear Information System (INIS)

Lassen, B C; Kuhnigk, J-M; Van Ginneken, B; Van Rikxoort, E M; Jacobs, C

2015-01-01

The malignancy of lung nodules is most often detected by analyzing changes of the nodule diameter in follow-up scans. A recent study showed that comparing the volume or the mass of a nodule over time is much more significant than comparing the diameter. Since the survival rate is higher when the disease is still in an early stage it is important to detect the growth rate as soon as possible. However manual segmentation of a volume is time-consuming. Whereas there are several well evaluated methods for the segmentation of solid nodules, less work is done on subsolid nodules which actually show a higher malignancy rate than solid nodules. In this work we present a fast, semi-automatic method for segmentation of subsolid nodules. As minimal user interaction the method expects a user-drawn stroke on the largest diameter of the nodule. First, a threshold-based region growing is performed based on intensity analysis of the nodule region and surrounding parenchyma. In the next step the chest wall is removed by a combination of a connected component analyses and convex hull calculation. Finally, attached vessels are detached by morphological operations. The method was evaluated on all nodules of the publicly available LIDC/IDRI database that were manually segmented and rated as non-solid or part-solid by four radiologists (Dataset 1) and three radiologists (Dataset 2). For these 59 nodules the Jaccard index for the agreement of the proposed method with the manual reference segmentations was 0.52/0.50 (Dataset 1/Dataset 2) compared to an inter-observer agreement of the manual segmentations of 0.54/0.58 (Dataset 1/Dataset 2). Furthermore, the inter-observer agreement using the proposed method (i.e. different input strokes) was analyzed and gave a Jaccard index of 0.74/0.74 (Dataset 1/Dataset 2). The presented method provides satisfactory segmentation results with minimal observer effort in minimal time and can reduce the inter-observer variability for segmentation of

Robust semi-automatic segmentation of pulmonary subsolid nodules in chest computed tomography scans

Science.gov (United States)

Lassen, B. C.; Jacobs, C.; Kuhnigk, J.-M.; van Ginneken, B.; van Rikxoort, E. M.

2015-02-01

The malignancy of lung nodules is most often detected by analyzing changes of the nodule diameter in follow-up scans. A recent study showed that comparing the volume or the mass of a nodule over time is much more significant than comparing the diameter. Since the survival rate is higher when the disease is still in an early stage it is important to detect the growth rate as soon as possible. However manual segmentation of a volume is time-consuming. Whereas there are several well evaluated methods for the segmentation of solid nodules, less work is done on subsolid nodules which actually show a higher malignancy rate than solid nodules. In this work we present a fast, semi-automatic method for segmentation of subsolid nodules. As minimal user interaction the method expects a user-drawn stroke on the largest diameter of the nodule. First, a threshold-based region growing is performed based on intensity analysis of the nodule region and surrounding parenchyma. In the next step the chest wall is removed by a combination of a connected component analyses and convex hull calculation. Finally, attached vessels are detached by morphological operations. The method was evaluated on all nodules of the publicly available LIDC/IDRI database that were manually segmented and rated as non-solid or part-solid by four radiologists (Dataset 1) and three radiologists (Dataset 2). For these 59 nodules the Jaccard index for the agreement of the proposed method with the manual reference segmentations was 0.52/0.50 (Dataset 1/Dataset 2) compared to an inter-observer agreement of the manual segmentations of 0.54/0.58 (Dataset 1/Dataset 2). Furthermore, the inter-observer agreement using the proposed method (i.e. different input strokes) was analyzed and gave a Jaccard index of 0.74/0.74 (Dataset 1/Dataset 2). The presented method provides satisfactory segmentation results with minimal observer effort in minimal time and can reduce the inter-observer variability for segmentation of

Operating manual for the critical experiments facility

International Nuclear Information System (INIS)

1986-01-01

The operation of the Critical Experiments Facility (CEF) requires careful attention to procedures in order that all safety precautions are observed. Since an accident could release large amounts of radioactivity, careful operation and strict enforcement of procedures are necessary. To provide for safe operation, detailed procedures have been written for all phases of the operation of this facility. The CEF operating procedures are not to be construed to constitute a part ofthe Technical Specifications. In the event of any discrepancy between the information given herein and the Technical Specifications, limits set forth in the Technical Specifications apply. All normal and most emergency operation conditions are covered by procedures presented in this manual. These procedures are designed to be followed by the operating personnel. Strict adherence to these procedures is expected for the following reasons. (1) To provide a standard, safe method of performing all operations, the procedures were written by reactor engineers experienced in supervising the operation of reactors and were reviewed by an organization with over 30 years of reactor operating experience. (2) To have an up-to-date description of operating techniques available at all times for reference and review, it is necessary that the procedures be written

Operating manual for the critical experiments facility

Energy Technology Data Exchange (ETDEWEB)

1986-01-01

The operation of the Critical Experiments Facility (CEF) requires careful attention to procedures in order that all safety precautions are observed. Since an accident could release large amounts of radioactivity, careful operation and strict enforcement of procedures are necessary. To provide for safe operation, detailed procedures have been written for all phases of the operation of this facility. The CEF operating procedures are not to be construed to constitute a part ofthe Technical Specifications. In the event of any discrepancy between the information given herein and the Technical Specifications, limits set forth in the Technical Specifications apply. All normal and most emergency operation conditions are covered by procedures presented in this manual. These procedures are designed to be followed by the operating personnel. Strict adherence to these procedures is expected for the following reasons. (1) To provide a standard, safe method of performing all operations, the procedures were written by reactor engineers experienced in supervising the operation of reactors and were reviewed by an organization with over 30 years of reactor operating experience. (2) To have an up-to-date description of operating techniques available at all times for reference and review, it is necessary that the procedures be written.

Operations and Maintenance Manual, Atmospheric Contaminant Sensor, Revision B.

Science.gov (United States)

National Aeronautics and Space Administration, Washington, DC.

The sensor is a mass spectrometer system which continuously monitors the atmospheric constituents of hydrogen, water vapor, nitrogen, oxygen, and carbon dioxide, and monitors the Freons on a demand sampling basis. The manual provides a system description, operational procedures, and maintenance and troubleshooting instructions. Circuit diagrams…

User-guided segmentation for volumetric retinal optical coherence tomography images

Science.gov (United States)

Yin, Xin; Chao, Jennifer R.; Wang, Ruikang K.

2014-01-01

Abstract. Despite the existence of automatic segmentation techniques, trained graders still rely on manual segmentation to provide retinal layers and features from clinical optical coherence tomography (OCT) images for accurate measurements. To bridge the gap between this time-consuming need of manual segmentation and currently available automatic segmentation techniques, this paper proposes a user-guided segmentation method to perform the segmentation of retinal layers and features in OCT images. With this method, by interactively navigating three-dimensional (3-D) OCT images, the user first manually defines user-defined (or sketched) lines at regions where the retinal layers appear very irregular for which the automatic segmentation method often fails to provide satisfactory results. The algorithm is then guided by these sketched lines to trace the entire 3-D retinal layer and anatomical features by the use of novel layer and edge detectors that are based on robust likelihood estimation. The layer and edge boundaries are finally obtained to achieve segmentation. Segmentation of retinal layers in mouse and human OCT images demonstrates the reliability and efficiency of the proposed user-guided segmentation method. PMID:25147962

Operation and maintenance manual for data acquisition system of MIDAS

International Nuclear Information System (INIS)

Lee, D. Y.; Park, W. M.; Kim, J. T.; Euh, D. J.

2001-09-01

This report describes an operation and maintenance manual of the data acquisition system and the data processing system for the DVI performance evaluation facility, MIDAS. The data acquisition system is implemented with VXI based system of Kinetic Systems TM , and the data processing PC. This report presents the configuration method and operation procedure for the operator. The modification procedure and method for functional extension and performance modification are also included for the future demand

Is STAPLE algorithm confident to assess segmentation methods in PET imaging?

International Nuclear Information System (INIS)

Dewalle-Vignion, Anne-Sophie; Betrouni, Nacim; Vermandel, Maximilien; Baillet, Clio

2015-01-01

Accurate tumor segmentation in [18F]-fluorodeoxyglucose positron emission tomography is crucial for tumor response assessment and target volume definition in radiation therapy. Evaluation of segmentation methods from clinical data without ground truth is usually based on physicians’ manual delineations. In this context, the simultaneous truth and performance level estimation (STAPLE) algorithm could be useful to manage the multi-observers variability. In this paper, we evaluated how this algorithm could accurately estimate the ground truth in PET imaging.Complete evaluation study using different criteria was performed on simulated data. The STAPLE algorithm was applied to manual and automatic segmentation results. A specific configuration of the implementation provided by the Computational Radiology Laboratory was used.Consensus obtained by the STAPLE algorithm from manual delineations appeared to be more accurate than manual delineations themselves (80% of overlap). An improvement of the accuracy was also observed when applying the STAPLE algorithm to automatic segmentations results.The STAPLE algorithm, with the configuration used in this paper, is more appropriate than manual delineations alone or automatic segmentations results alone to estimate the ground truth in PET imaging. Therefore, it might be preferred to assess the accuracy of tumor segmentation methods in PET imaging. (paper)

Is STAPLE algorithm confident to assess segmentation methods in PET imaging?

Science.gov (United States)

Dewalle-Vignion, Anne-Sophie; Betrouni, Nacim; Baillet, Clio; Vermandel, Maximilien

2015-12-01

Accurate tumor segmentation in [18F]-fluorodeoxyglucose positron emission tomography is crucial for tumor response assessment and target volume definition in radiation therapy. Evaluation of segmentation methods from clinical data without ground truth is usually based on physicians’ manual delineations. In this context, the simultaneous truth and performance level estimation (STAPLE) algorithm could be useful to manage the multi-observers variability. In this paper, we evaluated how this algorithm could accurately estimate the ground truth in PET imaging. Complete evaluation study using different criteria was performed on simulated data. The STAPLE algorithm was applied to manual and automatic segmentation results. A specific configuration of the implementation provided by the Computational Radiology Laboratory was used. Consensus obtained by the STAPLE algorithm from manual delineations appeared to be more accurate than manual delineations themselves (80% of overlap). An improvement of the accuracy was also observed when applying the STAPLE algorithm to automatic segmentations results. The STAPLE algorithm, with the configuration used in this paper, is more appropriate than manual delineations alone or automatic segmentations results alone to estimate the ground truth in PET imaging. Therefore, it might be preferred to assess the accuracy of tumor segmentation methods in PET imaging.

SU-E-J-168: Automated Pancreas Segmentation Based On Dynamic MRI

International Nuclear Information System (INIS)

Gou, S; Rapacchi, S; Hu, P; Sheng, K

2014-01-01

Purpose: MRI guided radiotherapy is particularly attractive for abdominal targets with low CT contrast. To fully utilize this modality for pancreas tracking, automated segmentation tools are needed. A hybrid gradient, region growth and shape constraint (hGReS) method to segment 2D upper abdominal dynamic MRI is developed for this purpose. Methods: 2D coronal dynamic MR images of 2 healthy volunteers were acquired with a frame rate of 5 f/second. The regions of interest (ROIs) included the liver, pancreas and stomach. The first frame was used as the source where the centers of the ROIs were annotated. These center locations were propagated to the next dynamic MRI frame. 4-neighborhood region transfer growth was performed from these initial seeds for rough segmentation. To improve the results, gradient, edge and shape constraints were applied to the ROIs before final refinement using morphological operations. Results from hGReS and 3 other automated segmentation methods using edge detection, region growth and level set were compared to manual contouring. Results: For the first patient, hGReS resulted in the organ segmentation accuracy as measure by the Dices index (0.77) for the pancreas. The accuracy was slightly superior to the level set method (0.72), and both are significantly more accurate than the edge detection (0.53) and region growth methods (0.42). For the second healthy volunteer, hGReS reliably segmented the pancreatic region, achieving a Dices index of 0.82, 0.92 and 0.93 for the pancreas, stomach and liver, respectively, comparing to manual segmentation. Motion trajectories derived from the hGReS, level set and manual segmentation methods showed high correlation to respiratory motion calculated using a lung blood vessel as the reference while the other two methods showed substantial motion tracking errors. hGReS was 10 times faster than level set. Conclusion: We have shown the feasibility of automated segmentation of the pancreas anatomy based on

Controlatron Neutron Tube Test Suite Software Manual - Operation Manual (V2.2)

CERN Document Server

Noel, W P; Hertrich, R J; Martinez, M L; Wallace, D L

2002-01-01

The Controlatron Software Suite is a custom built application to perform automated testing of Controlatron neutron tubes. The software package was designed to allowing users to design tests and to run a series of test suites on a tube. The data is output to ASCII files of a pre-defined format for data analysis and viewing with the Controlatron Data Viewer Application. This manual discusses the operation of the Controlatron Test Suite Software and a brief discussion of state machine theory, as state machine is the functional basis of the software.

Polarized proton Target-III operators manual, revision A

International Nuclear Information System (INIS)

Hill, D.; Moretti, A.; Onesto, F.; Rynes, P.

1976-04-01

A revision is given of a manual containing standard operating procedures for the vacuum, cryogenic, and electronic systems of a polarized proton target. The discussion includes the target cryostat, the 3 He and 4 He pumping systems, remote monitors and controls, the microwave system, the magnet and power supply, the computerized polarization monitor, the 4 He liquifier and gas recovery system, and miscellaneous auxiliary equipment

Computerized low-level waste assay system operation manual

International Nuclear Information System (INIS)

Jones, D.F.; Cowder, L.R.; Martin, E.R.

1976-01-01

An operation and maintenance manual for the computerized low-level waste box counter is presented, which describes routine assay techniques as well as theory of operation treated in sufficient depth so that an experienced assayist can make nonroutine assays. In addition, complete system schematics are included, along with a complete circuit description to facilitate not only maintenance and troubleshooting, but also reproduction of the instrument if desired. Complete software system descriptions are included so far as calculational algorithms are concerned, although detailed instruction listings would have to be obtained from Group R-1 at LASL in order to make machine-language code changes

Operation Manual of the high voltage generator of the Pelletron electron accelerator

International Nuclear Information System (INIS)

Hernandez M, V.; Lopez V, H.; Alba P, U.

1988-04-01

The first version of a manual to operate the generator of high voltage generator of the Pelletron electron accelerator built in the ININ is presented. Since this generator has several components and/or elements, the one manual present has the purpose that the armed one or maintenance of anyone on its parts, is carried out in an orderly and efficient way. (Author)

A new framework for interactive images segmentation

International Nuclear Information System (INIS)

Ashraf, M.; Sarim, M.; Shaikh, A.B.

2017-01-01

Image segmentation has become a widely studied research problem in image processing. There exist different graph based solutions for interactive image segmentation but the domain of image segmentation still needs persistent improvements. The segmentation quality of existing techniques generally depends on the manual input provided in beginning, therefore, these algorithms may not produce quality segmentation with initial seed labels provided by a novice user. In this work we investigated the use of cellular automata in image segmentation and proposed a new algorithm that follows a cellular automaton in label propagation. It incorporates both the pixel's local and global information in the segmentation process. We introduced the novel global constraints in automata evolution rules; hence proposed scheme of automata evolution is more effective than the automata based earlier evolution schemes. Global constraints are also effective in deceasing the sensitivity towards small changes made in manual input; therefore proposed approach is less dependent on label seed marks. It can produce the quality segmentation with modest user efforts. Segmentation results indicate that the proposed algorithm performs better than the earlier segmentation techniques. (author)

A multi-atlas based method for automated anatomical rat brain MRI segmentation and extraction of PET activity.

Science.gov (United States)

Lancelot, Sophie; Roche, Roxane; Slimen, Afifa; Bouillot, Caroline; Levigoureux, Elise; Langlois, Jean-Baptiste; Zimmer, Luc; Costes, Nicolas

2014-01-01

Preclinical in vivo imaging requires precise and reproducible delineation of brain structures. Manual segmentation is time consuming and operator dependent. Automated segmentation as usually performed via single atlas registration fails to account for anatomo-physiological variability. We present, evaluate, and make available a multi-atlas approach for automatically segmenting rat brain MRI and extracting PET activies. High-resolution 7T 2DT2 MR images of 12 Sprague-Dawley rat brains were manually segmented into 27-VOI label volumes using detailed protocols. Automated methods were developed with 7/12 atlas datasets, i.e. the MRIs and their associated label volumes. MRIs were registered to a common space, where an MRI template and a maximum probability atlas were created. Three automated methods were tested: 1/registering individual MRIs to the template, and using a single atlas (SA), 2/using the maximum probability atlas (MP), and 3/registering the MRIs from the multi-atlas dataset to an individual MRI, propagating the label volumes and fusing them in individual MRI space (propagation & fusion, PF). Evaluation was performed on the five remaining rats which additionally underwent [18F]FDG PET. Automated and manual segmentations were compared for morphometric performance (assessed by comparing volume bias and Dice overlap index) and functional performance (evaluated by comparing extracted PET measures). Only the SA method showed volume bias. Dice indices were significantly different between methods (PF>MP>SA). PET regional measures were more accurate with multi-atlas methods than with SA method. Multi-atlas methods outperform SA for automated anatomical brain segmentation and PET measure's extraction. They perform comparably to manual segmentation for FDG-PET quantification. Multi-atlas methods are suitable for rapid reproducible VOI analyses.

Multicenter reliability of semiautomatic retinal layer segmentation using OCT

Science.gov (United States)

Oberwahrenbrock, Timm; Traber, Ghislaine L.; Lukas, Sebastian; Gabilondo, Iñigo; Nolan, Rachel; Songster, Christopher; Balk, Lisanne; Petzold, Axel; Paul, Friedemann; Villoslada, Pablo; Brandt, Alexander U.; Green, Ari J.

2018-01-01

Objective To evaluate the inter-rater reliability of semiautomated segmentation of spectral domain optical coherence tomography (OCT) macular volume scans. Methods Macular OCT volume scans of left eyes from 17 subjects (8 patients with MS and 9 healthy controls) were automatically segmented by Heidelberg Eye Explorer (v1.9.3.0) beta-software (Spectralis Viewing Module v6.0.0.7), followed by manual correction by 5 experienced operators from 5 different academic centers. The mean thicknesses within a 6-mm area around the fovea were computed for the retinal nerve fiber layer, ganglion cell layer (GCL), inner plexiform layer (IPL), inner nuclear layer, outer plexiform layer (OPL), and outer nuclear layer (ONL). Intraclass correlation coefficients (ICCs) were calculated for mean layer thickness values. Spatial distribution of ICC values for the segmented volume scans was investigated using heat maps. Results Agreement between raters was good (ICC > 0.84) for all retinal layers, particularly inner retinal layers showed excellent agreement across raters (ICC > 0.96). Spatial distribution of ICC showed highest values in the perimacular area, whereas the ICCs were poorer for the foveola and the more peripheral macular area. The automated segmentation of the OPL and ONL required the most correction and showed the least agreement, whereas differences were less prominent for the remaining layers. Conclusions Automated segmentation with manual correction of macular OCT scans is highly reliable when performed by experienced raters and can thus be applied in multicenter settings. Reliability can be improved by restricting analysis to the perimacular area and compound segmentation of GCL and IPL. PMID:29552598

Segmenting articular cartilage automatically using a voxel classification approach

DEFF Research Database (Denmark)

Folkesson, Jenny; Dam, Erik B; Olsen, Ole F

2007-01-01

We present a fully automatic method for articular cartilage segmentation from magnetic resonance imaging (MRI) which we use as the foundation of a quantitative cartilage assessment. We evaluate our method by comparisons to manual segmentations by a radiologist and by examining the interscan...... reproducibility of the volume and area estimates. Training and evaluation of the method is performed on a data set consisting of 139 scans of knees with a status ranging from healthy to severely osteoarthritic. This is, to our knowledge, the only fully automatic cartilage segmentation method that has good...... agreement with manual segmentations, an interscan reproducibility as good as that of a human expert, and enables the separation between healthy and osteoarthritic populations. While high-field scanners offer high-quality imaging from which the articular cartilage have been evaluated extensively using manual...

Manual for IRS Coding. Joint IAEA/NEA International Reporting System for Operating Experience

International Nuclear Information System (INIS)

2011-01-01

The International Reporting System for Operating Experience (IRS) is jointly operated by the International Atomic Energy Agency (IAEA) and the Nuclear Energy Agency of the Organisation for Economic Co-operation and Development (OECD/NEA). In early 2010, the IAEA and OECD/NEA jointly issued the IRS Guidelines, which described the reporting system and process and gave users the necessary elements to enable them to produce IRS reports to a high standard of quality while retaining the effectiveness of the system expected by all Member States operating nuclear power plants. The purpose of the present Manual for IRS Coding is to provide supplementary guidance specifically on the coding element of IRS reports to ensure uniform coding of events that are reported through IRS. This Coding Manual does not supersede the IRS Guidelines, but rather, supports users and preparers in achieving a consistent and high level of quality in their IRS reports. Consistency and high quality in the IRS reports allow stakeholders to search and retrieve specific event information with ease. In addition, well-structured reports also enhance the efficient management of the IRS database. This Coding Manual will give specific guidance on the application of each section of the IRS codes, with examples where necessary, of when and how these codes are to be applied. As this reporting system is owned by the Member States, this manual has been developed and approved by the IRS National Coordinators with the assistance of the IAEA and NEA secretariats

Operating manual for the Tower Shielding Facility

International Nuclear Information System (INIS)

1985-12-01

This manual provides information necessary to operate and perform maintenance on the reactor systems and all equipment or systems which can affect their operation or the safety of personnel at the Tower Shielding Facility. The first four chapters consist of introductory and descriptive material of benefit to personnel in training, the qualifications required for training, the responsibilities of the personnel in the organization, and the procedures for reviewing proposed experiments. Chapter 8, Emergency Procedures, is also a necessary part of the indoctrination of personnel. The procedures for operation of the Tower Shielding Reactor (TSR-II), its water cooling system, and the main tower hoists are outlined in Chapters 5, 6, and 7. The Technical Specification surveillance requirements for the TSR-II are summarized in Chapter 9. The maintenance and calibration schedule is spelled out in Chapter 10. The procedures for assembly and disassembly of the TSR-II are outlined in Chapter 11

Segmentation-DrivenTomographic Reconstruction

DEFF Research Database (Denmark)

Kongskov, Rasmus Dalgas

such that the segmentation subsequently can be carried out by use of a simple segmentation method, for instance just a thresholding method. We tested the advantages of going from a two-stage reconstruction method to a one stage segmentation-driven reconstruction method for the phase contrast tomography reconstruction......The tomographic reconstruction problem is concerned with creating a model of the interior of an object from some measured data, typically projections of the object. After reconstructing an object it is often desired to segment it, either automatically or manually. For computed tomography (CT...

SNAP operating system reference manual

International Nuclear Information System (INIS)

Sabuda, J.D.; Polito, J.; Walker, J.L.; Grant, F.H. III.

1982-03-01

The SNAP Operating System (SOS) is a FORTRAN 77 program which provides assistance to the safeguards analyst who uses the Safeguards Automated Facility Evaluation (SAFE) and the Safeguards Network Analysis Procedure (SNAP) techniques. Features offered by SOS are a data base system for storing a library of SNAP applications, computer graphics representation of SNAP models, a computer graphics editor to develop and modify SNAP models, a SAFE-to-SNAP interface, automatic generation of SNAP input data, and a computer graphic post-processor for SNAP. The SOS Reference Manual provides detailed application information concerning SOS as well as a detailed discussion of all SOS components and their associated command input formats. SOS was developed for the US Nuclear Regulatory Commission's Office of Nuclear Regulatory Research and the US Naval Surface Weapons Center by Pritsker and Associates, Inc., under contract to Sandia National Laboratories

Hemorrhage Detection and Segmentation in Traumatic Pelvic Injuries

Science.gov (United States)

Davuluri, Pavani; Wu, Jie; Tang, Yang; Cockrell, Charles H.; Ward, Kevin R.; Najarian, Kayvan; Hargraves, Rosalyn H.

2012-01-01

Automated hemorrhage detection and segmentation in traumatic pelvic injuries is vital for fast and accurate treatment decision making. Hemorrhage is the main cause of deaths in patients within first 24 hours after the injury. It is very time consuming for physicians to analyze all Computed Tomography (CT) images manually. As time is crucial in emergence medicine, analyzing medical images manually delays the decision-making process. Automated hemorrhage detection and segmentation can significantly help physicians to analyze these images and make fast and accurate decisions. Hemorrhage segmentation is a crucial step in the accurate diagnosis and treatment decision-making process. This paper presents a novel rule-based hemorrhage segmentation technique that utilizes pelvic anatomical information to segment hemorrhage accurately. An evaluation measure is used to quantify the accuracy of hemorrhage segmentation. The results show that the proposed method is able to segment hemorrhage very well, and the results are promising. PMID:22919433

Using simulated fluorescence cell micrographs for the evaluation of cell image segmentation algorithms.

Science.gov (United States)

Wiesmann, Veit; Bergler, Matthias; Palmisano, Ralf; Prinzen, Martin; Franz, Daniela; Wittenberg, Thomas

2017-03-18

Manual assessment and evaluation of fluorescent micrograph cell experiments is time-consuming and tedious. Automated segmentation pipelines can ensure efficient and reproducible evaluation and analysis with constant high quality for all images of an experiment. Such cell segmentation approaches are usually validated and rated in comparison to manually annotated micrographs. Nevertheless, manual annotations are prone to errors and display inter- and intra-observer variability which influence the validation results of automated cell segmentation pipelines. We present a new approach to simulate fluorescent cell micrographs that provides an objective ground truth for the validation of cell segmentation methods. The cell simulation was evaluated twofold: (1) An expert observer study shows that the proposed approach generates realistic fluorescent cell micrograph simulations. (2) An automated segmentation pipeline on the simulated fluorescent cell micrographs reproduces segmentation performances of that pipeline on real fluorescent cell micrographs. The proposed simulation approach produces realistic fluorescent cell micrographs with corresponding ground truth. The simulated data is suited to evaluate image segmentation pipelines more efficiently and reproducibly than it is possible on manually annotated real micrographs.

LANDSAT-D ground segment operations plan, revision A

Science.gov (United States)

Evans, B.

1982-01-01

The basic concept for the utilization of LANDSAT ground processing resources is described. Only the steady state activities that support normal ground processing are addressed. This ground segment operations plan covers all processing of the multispectral scanner and the processing of thematic mapper through data acquisition and payload correction data generation for the LANDSAT 4 mission. The capabilities embedded in the hardware and software elements are presented from an operations viewpoint. The personnel assignments associated with each functional process and the mechanisms available for controlling the overall data flow are identified.

Fuel Rod Consolidation Project: Phase 2, Final report: Volume 5, Operations and maintenance manual

International Nuclear Information System (INIS)

1988-01-01

The purpose of this manual is to describe the function, installation, operation and maintenance of the Fuel Rod Consolidation System. This Document is preliminary and must be updated to incorporate any modifications to the mechanical and electrical systems that are performed during construction. Any changes and specific references related to the software requirements will be provided as the software is developed in Phase III. Setpoints related to equipment positions as a function of resolver and position transducer readings will also be provided in Phase III. References such as vendor supplied Operating and Maintenance Manuals for vendor components and assemblies are not available until a receipt of a purchase order. These references will become an integral part of this manual during the construction phase

Polarized proton target-III. Operations manual, revision B

International Nuclear Information System (INIS)

Hill, D.; Moretti, A.; Onesto, F.; Rynes, P.

1978-01-01

The manual presented contains certain standard operating procedures for the vacuum, cryogenic, and electronic systems of PPT-III. In total, these systems comprise the following major divisions: (1) the target cryostat; (2) the 4 He pumping system; (3) the 3 He pumping system; (4) the remote monitors and controls; (5) the microwave system; (6) the magnet and power supply; (7) the computerized polarization monitor; (8) the 4 He liquefier and gas recovery system; and (9) miscellaneous auxiliary equipment

Exploratory analysis of genomic segmentations with Segtools

Directory of Open Access Journals (Sweden)

Buske Orion J

2011-10-01

Full Text Available Abstract Background As genome-wide experiments and annotations become more prevalent, researchers increasingly require tools to help interpret data at this scale. Many functional genomics experiments involve partitioning the genome into labeled segments, such that segments sharing the same label exhibit one or more biochemical or functional traits. For example, a collection of ChlP-seq experiments yields a compendium of peaks, each labeled with one or more associated DNA-binding proteins. Similarly, manually or automatically generated annotations of functional genomic elements, including cis-regulatory modules and protein-coding or RNA genes, can also be summarized as genomic segmentations. Results We present a software toolkit called Segtools that simplifies and automates the exploration of genomic segmentations. The software operates as a series of interacting tools, each of which provides one mode of summarization. These various tools can be pipelined and summarized in a single HTML page. We describe the Segtools toolkit and demonstrate its use in interpreting a collection of human histone modification data sets and Plasmodium falciparum local chromatin structure data sets. Conclusions Segtools provides a convenient, powerful means of interpreting a genomic segmentation.

Instruction manual for operating the Sensys System for temporary traffic counts

Science.gov (United States)

2010-01-01

This instruction manual provides information and the procedures for using the Sensys System, which was initially designed to operate in a server controlled network, for temporary traffic counts. The instructions will allow the user to fully understan...

TMI cable tracer operation and maintenance manual for assembly 417910

International Nuclear Information System (INIS)

Sumstine, R.L.

1983-11-01

This manual provides technical information and instructions to operate and maintain the cable tracer designed for the Three Mile Island (TMI) Unit 2 Reactor Building. The TMI cable tracer was developed to allow TMI personnel to trace cables in cable trays that may be tested or sectioned for destructive examination

Coulometer operator's manual

International Nuclear Information System (INIS)

Criscuolo, A.L.

1977-07-01

The coulometer control system automates the titration of uranium and plutonium as performed by the CMB-1 group. The system consists of a printer, microcontroller, and coulometer, all of which are controlled by an algorithm stored in the microcontroller read-only memory. This manual describes the titration procedure using the coulometer control system, its theory and maintenance

Three-dimensional lung tumor segmentation from x-ray computed tomography using sparse field active models.

Science.gov (United States)

Awad, Joseph; Owrangi, Amir; Villemaire, Lauren; O'Riordan, Elaine; Parraga, Grace; Fenster, Aaron

2012-02-01

.65%-5.88%) and manual observers (4.20%-6.61%, 8.14%-9.57%, and 14.57%-21.61%) for 1D, 2D, and 3D measurements, respectively. The authors developed an automated segmentation algorithm requiring only that the operator select the tumor to measure pulmonary metastatic tumors in 1D, 2D, and 3D. Algorithm and manual measurements were significantly correlated. Since the algorithm segmentation involves selection of a single seed point, it resulted in reduced intra-observer variability and decreased time, for making the measurements.

AUDIT DISCLOSURE OF MATERIAL INFORMATION ON OPERATING SEGMENTS THE ACTIVITIES OF THE ORGANIZATIONS OF TOURIST SPHERE

Directory of Open Access Journals (Sweden)

Екатерина Николаевна Скорикова

2013-04-01

Full Text Available In modern conditions market economy for take decisions of use services tourist organizations, users not enough relevant information of financial result activities.The article considered audit disclosure relevant information on operating segments activities, for example tourist organizations.In result research considered operating segments on current and discontinued activities, and their impact on disclosure relevant information of financial result.Proposed option disclosure relevant information on operating segments activities in explanatory Note to the annual financial statements.Received results prove, that information on operating segments activities essential in all aspects.Results research has as theoretical so and practical significance, and can used at further development theoretical and practical questions on disclosure relevant information of activities organizations of tourist sphere.DOI: http://dx.doi.org/10.12731/2218-7405-2013-1-2

Segmentation of Brain Lesions in MRI and CT Scan Images: A Hybrid Approach Using k-Means Clustering and Image Morphology

Science.gov (United States)

Agrawal, Ritu; Sharma, Manisha; Singh, Bikesh Kumar

2018-04-01

Manual segmentation and analysis of lesions in medical images is time consuming and subjected to human errors. Automated segmentation has thus gained significant attention in recent years. This article presents a hybrid approach for brain lesion segmentation in different imaging modalities by combining median filter, k means clustering, Sobel edge detection and morphological operations. Median filter is an essential pre-processing step and is used to remove impulsive noise from the acquired brain images followed by k-means segmentation, Sobel edge detection and morphological processing. The performance of proposed automated system is tested on standard datasets using performance measures such as segmentation accuracy and execution time. The proposed method achieves a high accuracy of 94% when compared with manual delineation performed by an expert radiologist. Furthermore, the statistical significance test between lesion segmented using automated approach and that by expert delineation using ANOVA and correlation coefficient achieved high significance values of 0.986 and 1 respectively. The experimental results obtained are discussed in lieu of some recently reported studies.

Interactive and scale invariant segmentation of the rectum/sigmoid via user-defined templates

Science.gov (United States)

Lüddemann, Tobias; Egger, Jan

2016-03-01

Among all types of cancer, gynecological malignancies belong to the 4th most frequent type of cancer among women. Besides chemotherapy and external beam radiation, brachytherapy is the standard procedure for the treatment of these malignancies. In the progress of treatment planning, localization of the tumor as the target volume and adjacent organs of risks by segmentation is crucial to accomplish an optimal radiation distribution to the tumor while simultaneously preserving healthy tissue. Segmentation is performed manually and represents a time-consuming task in clinical daily routine. This study focuses on the segmentation of the rectum/sigmoid colon as an Organ-At-Risk in gynecological brachytherapy. The proposed segmentation method uses an interactive, graph-based segmentation scheme with a user-defined template. The scheme creates a directed two dimensional graph, followed by the minimal cost closed set computation on the graph, resulting in an outlining of the rectum. The graphs outline is dynamically adapted to the last calculated cut. Evaluation was performed by comparing manual segmentations of the rectum/sigmoid colon to results achieved with the proposed method. The comparison of the algorithmic to manual results yielded to a Dice Similarity Coefficient value of 83.85+/-4.08%, in comparison to 83.97+/-8.08% for the comparison of two manual segmentations of the same physician. Utilizing the proposed methodology resulted in a median time of 128 seconds per dataset, compared to 300 seconds needed for pure manual segmentation.

Boundary segmentation for fluorescence microscopy using steerable filters

Science.gov (United States)

Ho, David Joon; Salama, Paul; Dunn, Kenneth W.; Delp, Edward J.

2017-02-01

Fluorescence microscopy is used to image multiple subcellular structures in living cells which are not readily observed using conventional optical microscopy. Moreover, two-photon microscopy is widely used to image structures deeper in tissue. Recent advancement in fluorescence microscopy has enabled the generation of large data sets of images at different depths, times, and spectral channels. Thus, automatic object segmentation is necessary since manual segmentation would be inefficient and biased. However, automatic segmentation is still a challenging problem as regions of interest may not have well defined boundaries as well as non-uniform pixel intensities. This paper describes a method for segmenting tubular structures in fluorescence microscopy images of rat kidney and liver samples using adaptive histogram equalization, foreground/background segmentation, steerable filters to capture directional tendencies, and connected-component analysis. The results from several data sets demonstrate that our method can segment tubular boundaries successfully. Moreover, our method has better performance when compared to other popular image segmentation methods when using ground truth data obtained via manual segmentation.

System administrator's manual (SAM) for the enhanced logistics intratheater support tool (ELIST) database instance segment version 8.1.0.0 for solaris 7.; TOPICAL

International Nuclear Information System (INIS)

Dritz, K.

2002-01-01

This document is the System Administrator's Manual (SAM) for the Enhanced Logistics Intratheater Support Tool (ELIST) Database Instance Segment. It covers errors that can arise during the segment's installation and deinstallation, and it outlines appropriate recovery actions. It also tells how to change the password for the SYSTEM account of the database instance after the instance is created, and it discusses the creation of a suitable database instance for ELIST by means other than the installation of the segment. The latter subject is covered in more depth than its introductory discussion in the Installation Procedures (IP) for the Enhanced Logistics Intratheater Support Tool (ELIST) Global Data Segment, Database Instance Segment, Database Fill Segment, Database Segment, Database Utility Segment, Software Segment, and Reference Data Segment (referred to in portions of this document as the ELIST IP). The information in this document is expected to be of use only rarely. Other than errors arising from the failure to follow instructions, difficulties are not expected to be encountered during the installation or deinstallation of the segment. By the same token, the need to create a database instance for ELIST by means other than the installation of the segment is expected to be the exception, rather than the rule. Most administrators will only need to be aware of the help that is provided in this document and will probably not actually need to read and make use of it

33 CFR 157.150 - Crude Oil Washing Operations and Equipment Manual: Recording information after inspections.

Science.gov (United States)

2010-07-01

... Equipment Manual: Recording information after inspections. 157.150 Section 157.150 Navigation and Navigable... Vessels Inspections § 157.150 Crude Oil Washing Operations and Equipment Manual: Recording information... machines. (2) Revolutions, number of cycles, and length of cycles of each COW machine. (3) Pressure and...

33 CFR 150.20 - How many copies of the operations manual must be given to the Coast Guard?

Science.gov (United States)

2010-07-01

... 33 Navigation and Navigable Waters 2 2010-07-01 2010-07-01 false How many copies of the operations manual must be given to the Coast Guard? 150.20 Section 150.20 Navigation and Navigable Waters COAST... § 150.20 How many copies of the operations manual must be given to the Coast Guard? The draft operations...

Automatic segmentation of thoracic and pelvic CT images for radiotherapy planning using implicit anatomic knowledge and organ-specific segmentation strategies

International Nuclear Information System (INIS)

Haas, B; Coradi, T; Scholz, M; Kunz, P; Huber, M; Oppitz, U; Andre, L; Lengkeek, V; Huyskens, D; Esch, A van; Reddick, R

2008-01-01

Automatic segmentation of anatomical structures in medical images is a valuable tool for efficient computer-aided radiotherapy and surgery planning and an enabling technology for dynamic adaptive radiotherapy. This paper presents the design, algorithms and validation of new software for the automatic segmentation of CT images used for radiotherapy treatment planning. A coarse to fine approach is followed that consists of presegmentation, anatomic orientation and structure segmentation. No user input or a priori information about the image content is required. In presegmentation, the body outline, the bones and lung equivalent tissue are detected. Anatomic orientation recognizes the patient's position, orientation and gender and creates an elastic mapping of the slice positions to a reference scale. Structure segmentation is divided into localization, outlining and refinement, performed by procedures with implicit anatomic knowledge using standard image processing operations. The presented version of algorithms automatically segments the body outline and bones in any gender and patient position, the prostate, bladder and femoral heads for male pelvis in supine position, and the spinal canal, lungs, heart and trachea in supine position. The software was developed and tested on a collection of over 600 clinical radiotherapy planning CT stacks. In a qualitative validation on this test collection, anatomic orientation correctly detected gender, patient position and body region in 98% of the cases, a correct mapping was produced for 89% of thorax and 94% of pelvis cases. The average processing time for the entire segmentation of a CT stack was less than 1 min on a standard personal computer. Two independent retrospective studies were carried out for clinical validation. Study I was performed on 66 cases (30 pelvis, 36 thorax) with dosimetrists, study II on 52 cases (39 pelvis, 13 thorax) with radio-oncologists as experts. The experts rated the automatically produced

OASIS is Automated Statistical Inference for Segmentation, with applications to multiple sclerosis lesion segmentation in MRI.

Science.gov (United States)

Sweeney, Elizabeth M; Shinohara, Russell T; Shiee, Navid; Mateen, Farrah J; Chudgar, Avni A; Cuzzocreo, Jennifer L; Calabresi, Peter A; Pham, Dzung L; Reich, Daniel S; Crainiceanu, Ciprian M

2013-01-01

Magnetic resonance imaging (MRI) can be used to detect lesions in the brains of multiple sclerosis (MS) patients and is essential for diagnosing the disease and monitoring its progression. In practice, lesion load is often quantified by either manual or semi-automated segmentation of MRI, which is time-consuming, costly, and associated with large inter- and intra-observer variability. We propose OASIS is Automated Statistical Inference for Segmentation (OASIS), an automated statistical method for segmenting MS lesions in MRI studies. We use logistic regression models incorporating multiple MRI modalities to estimate voxel-level probabilities of lesion presence. Intensity-normalized T1-weighted, T2-weighted, fluid-attenuated inversion recovery and proton density volumes from 131 MRI studies (98 MS subjects, 33 healthy subjects) with manual lesion segmentations were used to train and validate our model. Within this set, OASIS detected lesions with a partial area under the receiver operating characteristic curve for clinically relevant false positive rates of 1% and below of 0.59% (95% CI; [0.50%, 0.67%]) at the voxel level. An experienced MS neuroradiologist compared these segmentations to those produced by LesionTOADS, an image segmentation software that provides segmentation of both lesions and normal brain structures. For lesions, OASIS out-performed LesionTOADS in 74% (95% CI: [65%, 82%]) of cases for the 98 MS subjects. To further validate the method, we applied OASIS to 169 MRI studies acquired at a separate center. The neuroradiologist again compared the OASIS segmentations to those from LesionTOADS. For lesions, OASIS ranked higher than LesionTOADS in 77% (95% CI: [71%, 83%]) of cases. For a randomly selected subset of 50 of these studies, one additional radiologist and one neurologist also scored the images. Within this set, the neuroradiologist ranked OASIS higher than LesionTOADS in 76% (95% CI: [64%, 88%]) of cases, the neurologist 66% (95% CI: [52%, 78

Gamma-ray measurements with the segmented gamma scan

International Nuclear Information System (INIS)

Martin, E.R.; Jones, D.F.; Parker, J.L.

1977-12-01

A revised and updated operation and maintenance manual for the segmented gamma-scan instrument is presented, which describes routine assay techniques as well as the theory of operation in sufficient depth that an experienced assayist can make nonroutine assays on a wide variety of materials and samples. In addition, complete electronic and electrical schematics of the Los Alamos Scientific Laboratory (LASL)-designed portions of the system are presented, along with sufficient system and circuit description to facilitate maintenance and troubleshooting. Complete software system descriptions are included, although detailed listings would have to be obained from LASL in order to make machine-language code changes

Marker-controlled watershed for lymphoma segmentation in sequential CT images

International Nuclear Information System (INIS)

Yan Jiayong; Zhao Binsheng; Wang, Liang; Zelenetz, Andrew; Schwartz, Lawrence H.

2006-01-01

Segmentation of lymphoma containing lymph nodes is a difficult task because of multiple variables associated with the tumor's location, intensity distribution, and contrast to its surrounding tissues. In this paper, we present a reliable and practical marker-controlled watershed algorithm for semi-automated segmentation of lymphoma in sequential CT images. Robust determination of internal and external markers is the key to successful use of the marker-controlled watershed transform in the segmentation of lymphoma and is the focus of this work. The external marker in our algorithm is the circle enclosing the lymphoma in a single slice. The internal marker, however, is determined automatically by combining techniques including Canny edge detection, thresholding, morphological operation, and distance map estimation. To obtain tumor volume, the segmented lymphoma in the current slice needs to be propagated to the adjacent slice to help determine the external and internal markers for delineation of the lymphoma in that slice. The algorithm was applied to 29 lymphomas (size range, 9-53 mm in diameter; mean, 23 mm) in nine patients. A blinded radiologist manually delineated all lymphomas on all slices. The manual result served as the ''gold standard'' for comparison. Several quantitative methods were applied to objectively evaluate the performance of the segmentation algorithm. The algorithm received a mean overlap, overestimation, and underestimation ratios of 83.2%, 13.5%, and 5.5%, respectively. The mean average boundary distance and Hausdorff boundary distance were 0.7 and 3.7 mm. Preliminary results have shown the potential of this computer algorithm to allow reliable segmentation and quantification of lymphomas on sequential CT images

Evaluation of left atrial function by multidetector computed tomography before left atrial radiofrequency-catheter ablation: Comparison of a manual and automated 3D volume segmentation method

International Nuclear Information System (INIS)

Wolf, Florian; Ourednicek, Petr; Loewe, Christian; Richter, Bernhard; Goessinger, Heinz David; Gwechenberger, Marianne; Plank, Christina; Schernthaner, Ruediger Egbert; Toepker, Michael; Lammer, Johannes; Feuchtner, Gudrun M.

2010-01-01

Introduction: The purpose of this study was to compare a manual and automated 3D volume segmentation tool for evaluation of left atrial (LA) function by 64-slice multidetector-CT (MDCT). Methods and materials: In 33 patients with paroxysmal atrial fibrillation a MDCT scan was performed before radiofrequency-catheter ablation. Atrial function (minimal volume (LAmin), maximal volume (LAmax), stroke volume (SV), ejection fraction (EF)) was evaluated by two readers using a manual and an automatic tool and measurement time was evaluated. Results: Automated LA volume segmentation failed in one patient due to low LA enhancement (103HU). Mean LAmax, LAmin, SV and EF were 127.7 ml, 93 ml, 34.7 ml, 27.1% by the automated, and 122.7 ml, 89.9 ml, 32.8 ml, 26.3% by the manual method with no significant difference (p > 0.05) and high Pearsons correlation coefficients (r = 0.94, r = 0.94, r = 0.82 and r = 0.85, p < 0.0001), respectively. The automated method was significantly faster (p < 0.001). Interobserver variability was low for both methods with Pearson's correlation coefficients between 0.98 and 0.99 (p < 0.0001). Conclusions: Evaluation of LA volume and function with 64-slice MDCT is feasible with a very low interobserver variability. The automatic method is as accurate as the manual method but significantly less time consuming permitting a routine use in clinical practice before RF-catheter ablation.

Evaluation of left atrial function by multidetector computed tomography before left atrial radiofrequency-catheter ablation: Comparison of a manual and automated 3D volume segmentation method

Energy Technology Data Exchange (ETDEWEB)

Wolf, Florian, E-mail: florian.wolf@meduniwien.ac.a [Department of Radiology, Medical University of Vienna, Vienna (Austria); Ourednicek, Petr [Philips Medical Systems, Prague (Czech Republic); Loewe, Christian [Department of Radiology, Medical University of Vienna, Vienna (Austria); Richter, Bernhard; Goessinger, Heinz David; Gwechenberger, Marianne [Department of Cardiology, Medical University of Vienna, Vienna (Austria); Plank, Christina; Schernthaner, Ruediger Egbert; Toepker, Michael; Lammer, Johannes [Department of Radiology, Medical University of Vienna, Vienna (Austria); Feuchtner, Gudrun M. [Department of Radiology, Innsbruck Medical University, Innsbruck (Austria); Institute of Diagnostic Radiology, University Hospital Zurich (Switzerland)

2010-08-15

Introduction: The purpose of this study was to compare a manual and automated 3D volume segmentation tool for evaluation of left atrial (LA) function by 64-slice multidetector-CT (MDCT). Methods and materials: In 33 patients with paroxysmal atrial fibrillation a MDCT scan was performed before radiofrequency-catheter ablation. Atrial function (minimal volume (LAmin), maximal volume (LAmax), stroke volume (SV), ejection fraction (EF)) was evaluated by two readers using a manual and an automatic tool and measurement time was evaluated. Results: Automated LA volume segmentation failed in one patient due to low LA enhancement (103HU). Mean LAmax, LAmin, SV and EF were 127.7 ml, 93 ml, 34.7 ml, 27.1% by the automated, and 122.7 ml, 89.9 ml, 32.8 ml, 26.3% by the manual method with no significant difference (p > 0.05) and high Pearsons correlation coefficients (r = 0.94, r = 0.94, r = 0.82 and r = 0.85, p < 0.0001), respectively. The automated method was significantly faster (p < 0.001). Interobserver variability was low for both methods with Pearson's correlation coefficients between 0.98 and 0.99 (p < 0.0001). Conclusions: Evaluation of LA volume and function with 64-slice MDCT is feasible with a very low interobserver variability. The automatic method is as accurate as the manual method but significantly less time consuming permitting a routine use in clinical practice before RF-catheter ablation.

Human machine interface to manually drive rhombic like vehicles in remote handling operations

International Nuclear Information System (INIS)

Lopes, Pedro; Vale, Alberto; Ventura, Rodrigo

2015-01-01

In the thermonuclear experimental reactor ITER, a vehicle named CTS is designed to transport a container with activated components inside the buildings. In nominal operations, the CTS is autonomously guided under supervision. However, in some unexpected situations, such as in rescue and recovery operations, the autonomous mode must be overridden and the CTS must be remotely guided by an operator. The CTS is a rhombic-like vehicle, with two drivable and steerable wheels along its longitudinal axis, providing omni-directional capabilities. The rhombic kinematics correspond to four control variables, which are difficult to manage in manual mode operation. This paper proposes a Human Machine Interface (HMI) to remotely guide the vehicle in manual mode. The proposed solution is implemented using a HMI with an encoder connected to a micro-controller and an analog 2-axis joystick. Experimental results were obtained comparing the proposed solution with other controller devices in different scenarios and using a software platform that simulates the kinematics and dynamics of the vehicle. (authors)

Human machine interface to manually drive rhombic like vehicles in remote handling operations

Energy Technology Data Exchange (ETDEWEB)

Lopes, Pedro; Vale, Alberto [Instituto de Plasmas e Fusao Nuclear, Instituto Superior Tecnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa (Portugal); Ventura, Rodrigo [Institute for Systems and Robotics, Instituto Superior Tecnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa (Portugal)

2015-07-01

In the thermonuclear experimental reactor ITER, a vehicle named CTS is designed to transport a container with activated components inside the buildings. In nominal operations, the CTS is autonomously guided under supervision. However, in some unexpected situations, such as in rescue and recovery operations, the autonomous mode must be overridden and the CTS must be remotely guided by an operator. The CTS is a rhombic-like vehicle, with two drivable and steerable wheels along its longitudinal axis, providing omni-directional capabilities. The rhombic kinematics correspond to four control variables, which are difficult to manage in manual mode operation. This paper proposes a Human Machine Interface (HMI) to remotely guide the vehicle in manual mode. The proposed solution is implemented using a HMI with an encoder connected to a micro-controller and an analog 2-axis joystick. Experimental results were obtained comparing the proposed solution with other controller devices in different scenarios and using a software platform that simulates the kinematics and dynamics of the vehicle. (authors)

A martian case study of segmenting images automatically for granulometry and sedimentology, Part 2: Assessment

Science.gov (United States)

Karunatillake, Suniti; McLennan, Scott M.; Herkenhoff, Kenneth E.; Husch, Jonathan M.; Hardgrove, Craig; Skok, J. R.

2014-02-01

In a companion work, we bridge the gap between mature segmentation software used in terrestrial sedimentology and emergent planetary segmentation with an original algorithm optimized to segment whole images from the Microscopic Imager (MI) of the Mars Exploration Rovers (MER). In this work, we compare its semi-automated outcome with manual photoanalyses using unconsolidated sediment at Gusev and Meridiani Planum sites for geologic context. On average, our code and manual segmentation converge to within ∼10% in the number and total area of identified grains in a pseudo-random, single blind comparison of 50 samples. Unlike manual segmentation, it also locates finer grains in an image with internal consistency, enabling robust comparisons across geologic contexts. When implemented in Mathematica-8, the algorithm segments an entire MI image within minutes, surpassing the extent and speed possible with manual segmentation by about a factor of ten. These results indicate that our algorithm enables not only new sedimentological insight from the MER MI data, but also detailed sedimentology with the Mars Science Laboratory’s Mars Hand Lens Instrument.

The FLP microsatellite platform flight operations manual

CERN Document Server

2016-01-01

This book represents the Flight Operations Manual for a reusable microsatellite platform – the “Future Low-cost Platform” (FLP), developed at the University of Stuttgart, Germany. It provides a basic insight on the onboard software functions, the core data handling system and on the power, communications, attitude control and thermal subsystem of the platform. Onboard failure detection, isolation and recovery functions are treated in detail. The platform is suited for satellites in the 50-150 kg class and is baseline of the microsatellite “Flying Laptop” from the University. The book covers the essential information for ground operators to controls an FLP-based satellite applying international command and control standards (CCSDS and ECSS PUS). Furthermore it provides an overview on the Flight Control Center in Stuttgart and on the link to the German Space Agency DLR Ground Station which is used for early mission phases. Flight procedure and mission planning chapters complement the book. .

Automated breast segmentation in ultrasound computer tomography SAFT images

Science.gov (United States)

Hopp, T.; You, W.; Zapf, M.; Tan, W. Y.; Gemmeke, H.; Ruiter, N. V.

2017-03-01

Ultrasound Computer Tomography (USCT) is a promising new imaging system for breast cancer diagnosis. An essential step before further processing is to remove the water background from the reconstructed images. In this paper we present a fully-automated image segmentation method based on three-dimensional active contours. The active contour method is extended by applying gradient vector flow and encoding the USCT aperture characteristics as additional weighting terms. A surface detection algorithm based on a ray model is developed to initialize the active contour, which is iteratively deformed to capture the breast outline in USCT reflection images. The evaluation with synthetic data showed that the method is able to cope with noisy images, and is not influenced by the position of the breast and the presence of scattering objects within the breast. The proposed method was applied to 14 in-vivo images resulting in an average surface deviation from a manual segmentation of 2.7 mm. We conclude that automated segmentation of USCT reflection images is feasible and produces results comparable to a manual segmentation. By applying the proposed method, reproducible segmentation results can be obtained without manual interaction by an expert.

Automatic segmentation of mandible in panoramic x-ray.

Science.gov (United States)

Abdi, Amir Hossein; Kasaei, Shohreh; Mehdizadeh, Mojdeh

2015-10-01

As the panoramic x-ray is the most common extraoral radiography in dentistry, segmentation of its anatomical structures facilitates diagnosis and registration of dental records. This study presents a fast and accurate method for automatic segmentation of mandible in panoramic x-rays. In the proposed four-step algorithm, a superior border is extracted through horizontal integral projections. A modified Canny edge detector accompanied by morphological operators extracts the inferior border of the mandible body. The exterior borders of ramuses are extracted through a contour tracing method based on the average model of mandible. The best-matched template is fetched from the atlas of mandibles to complete the contour of left and right processes. The algorithm was tested on a set of 95 panoramic x-rays. Evaluating the results against manual segmentations of three expert dentists showed that the method is robust. It achieved an average performance of [Formula: see text] in Dice similarity, specificity, and sensitivity.

Development of an operational manual for a consultation-liaison psychiatry service.

Science.gov (United States)

Wand, Anne Pf; Sharma, Swapnil; Carpenter, Lindsay J; Gatsi, Mike

2018-02-01

Consultation-liaison psychiatry (CLP) services sit between mental health and the general hospital, and risk being poorly understood by both systems. The aim of this study was to develop an operational manual for a CLP service, which defined functions and governance. The CLP literature was reviewed with a focus on descriptions of CLP roles, organisational processes, quality measures and service development. The CLP team held service planning meetings and met with members of the mental health and hospital executives. Site visits and collaboration with other CLP services occurred in defining the roles of the CLP service and organisational governance. A CLP operational document was developed, including a description of the service, its functions, staff roles and governance. Procedural information such as the CLP timetable, referral process, triage and assessment, documentation, activity recording, quality assurance and relevant policies were outlined. The development of a dedicated operational manual for CLP clarified the roles, functions and governance of CLP within the general hospital and mental health systems. The development process facilitated the engagement of key clinicians and administrators of these systems, the determination of quality improvement targets and greater transparency and accountability.

Evaluation of an atlas-based automatic segmentation software for the delineation of brain organs at risk in a radiation therapy clinical context

International Nuclear Information System (INIS)

Isambert, Aurelie; Dhermain, Frederic; Bidault, Francois; Commowick, Olivier; Bondiau, Pierre-Yves; Malandain, Gregoire; Lefkopoulos, Dimitri

2008-01-01

Background and purpose: Conformal radiation therapy techniques require the delineation of volumes of interest, a time-consuming and operator-dependent task. In this work, we aimed to evaluate the potential interest of an atlas-based automatic segmentation software (ABAS) of brain organs at risk (OAR), when used under our clinical conditions. Materials and methods: Automatic and manual segmentations of the eyes, optic nerves, optic chiasm, pituitary gland, brain stem and cerebellum of 11 patients on T1-weighted magnetic resonance, 3-mm thick slice images were compared using the Dice similarity coefficient (DSC). The sensitivity and specificity of the ABAS were also computed and analysed from a radiotherapy point of view by splitting the ROC (Receiver Operating Characteristic) space into four sub-regions. Results: Automatic segmentation of OAR was achieved in 7-8 min. Excellent agreement was obtained between automatic and manual delineations for organs exceeding 7 cm 3 : the DSC was greater than 0.8. For smaller structures, the DSC was lower than 0.41. Conclusions: These tests demonstrated that this ABAS is a robust and reliable tool for automatic delineation of large structures under clinical conditions in our daily practice, even though the small structures must continue to be delineated manually by an expert

3D segmentation of liver, kidneys and spleen from CT images

International Nuclear Information System (INIS)

Bekes, G.; Fidrich, M.; Nyul, L.G.; Mate, E.; Kuba, A.

2007-01-01

The clinicians often need to segment the abdominal organs for radiotherapy planning. Manual segmentation of these organs is very time-consuming, therefore automated methods are desired. We developed a semi-automatic segmentation method to outline liver, spleen and kidneys. It works on CT images without contrast intake that are acquired with a routine clinical protocol. From an initial surface around a user defined seed point, the segmentation of the organ is obtained by an active surface algorithm. Pre- and post-processing steps are used to adapt the general method for specific organs. The evaluation results show that the accuracy of our method is about 90%, which can be further improved with little manual editing, and that the precision is slightly higher than that of manual contouring. Our method is accurate, precise and fast enough to use in the clinical practice. (orig.)

IFRS 8 – OPERATING SEGMENTS

Directory of Open Access Journals (Sweden)

BOCHIS LEONICA

2009-05-01

Full Text Available Segment reporting in accordance with IFRS 8 will be mandatory for annual financial statements covering periods beginning on or after 1 January 2009. The standards replaces IAS 14, Segment Reporting, from that date. The objective of IFRS 8 is to require

Computer-aided liver volumetry: performance of a fully-automated, prototype post-processing solution for whole-organ and lobar segmentation based on MDCT imaging.

Science.gov (United States)

Fananapazir, Ghaneh; Bashir, Mustafa R; Marin, Daniele; Boll, Daniel T

2015-06-01

To evaluate the performance of a prototype, fully-automated post-processing solution for whole-liver and lobar segmentation based on MDCT datasets. A polymer liver phantom was used to assess accuracy of post-processing applications comparing phantom volumes determined via Archimedes' principle with MDCT segmented datasets. For the IRB-approved, HIPAA-compliant study, 25 patients were enrolled. Volumetry performance compared the manual approach with the automated prototype, assessing intraobserver variability, and interclass correlation for whole-organ and lobar segmentation using ANOVA comparison. Fidelity of segmentation was evaluated qualitatively. Phantom volume was 1581.0 ± 44.7 mL, manually segmented datasets estimated 1628.0 ± 47.8 mL, representing a mean overestimation of 3.0%, automatically segmented datasets estimated 1601.9 ± 0 mL, representing a mean overestimation of 1.3%. Whole-liver and segmental volumetry demonstrated no significant intraobserver variability for neither manual nor automated measurements. For whole-liver volumetry, automated measurement repetitions resulted in identical values; reproducible whole-organ volumetry was also achieved with manual segmentation, p(ANOVA) 0.98. For lobar volumetry, automated segmentation improved reproducibility over manual approach, without significant measurement differences for either methodology, p(ANOVA) 0.95-0.99. Whole-organ and lobar segmentation results from manual and automated segmentation showed no significant differences, p(ANOVA) 0.96-1.00. Assessment of segmentation fidelity found that segments I-IV/VI showed greater segmentation inaccuracies compared to the remaining right hepatic lobe segments. Automated whole-liver segmentation showed non-inferiority of fully-automated whole-liver segmentation compared to manual approaches with improved reproducibility and post-processing duration; automated dual-seed lobar segmentation showed slight tendencies for underestimating the right hepatic lobe

Model-based segmentation of short-axis MR cardiac images

NARCIS (Netherlands)

Spreeuwers, Lieuwe Jan; Breeuwer, M.

Reliable automatic segmentation of MR cardiac images is still an important problem in medical image processing. Although image data quality has improved considerably during the last years, this segmentation is still considered a difficult problem. Manual segmentation is hardly an option as this is

Intraparenchymal hemorrhage segmentation from clinical head CT of patients with traumatic brain injury

Science.gov (United States)

Roy, Snehashis; Wilkes, Sean; Diaz-Arrastia, Ramon; Butman, John A.; Pham, Dzung L.

2015-03-01

Quantification of hemorrhages in head computed tomography (CT) images from patients with traumatic brain injury (TBI) has potential applications in monitoring disease progression and better understanding of the patho-physiology of TBI. Although manual segmentations can provide accurate measures of hemorrhages, the processing time and inter-rater variability make it infeasible for large studies. In this paper, we propose a fully automatic novel pipeline for segmenting intraparenchymal hemorrhages (IPH) from clinical head CT images. Unlike previous methods of model based segmentation or active contour techniques, we rely on relevant and matching examples from already segmented images by trained raters. The CT images are first skull-stripped. Then example patches from an "atlas" CT and its manual segmentation are used to learn a two-class sparse dictionary for hemorrhage and normal tissue. Next, for a given "subject" CT, a subject patch is modeled as a sparse convex combination of a few atlas patches from the dictionary. The same convex combination is applied to the atlas segmentation patches to generate a membership for the hemorrhages at each voxel. Hemorrhages are segmented from 25 subjects with various degrees of TBI. Results are compared with segmentations obtained from an expert rater. A median Dice coefficient of 0.85 between automated and manual segmentations is achieved. A linear fit between automated and manual volumes show a slope of 1.0047, indicating a negligible bias in volume estimation.

Automatic lung segmentation in the presence of alveolar collapse

Directory of Open Access Journals (Sweden)

Noshadi Areg

2017-09-01

Full Text Available Lung ventilation and perfusion analyses using chest imaging methods require a correct segmentation of the lung to offer anatomical landmarks for the physiological data. An automatic segmentation approach simplifies and accelerates the analysis. However, the segmentation of the lungs has shown to be difficult if collapsed areas are present that tend to share similar gray values with surrounding non-pulmonary tissue. Our goal was to develop an automatic segmentation algorithm that is able to approximate dorsal lung boundaries even if alveolar collapse is present in the dependent lung areas adjacent to the pleura. Computed tomography data acquired in five supine pigs with injured lungs were used for this purpose. First, healthy lung tissue was segmented using a standard 3D region growing algorithm. Further, the bones in the chest wall surrounding the lungs were segmented to find the contact points of ribs and pleura. Artificial boundaries of the dorsal lung were set by spline interpolation through these contact points. Segmentation masks of the entire lung including the collapsed regions were created by combining the splines with the segmentation masks of the healthy lung tissue through multiple morphological operations. The automatically segmented images were then evaluated by comparing them to manual segmentations and determining the Dice similarity coefficients (DSC as a similarity measure. The developed method was able to accurately segment the lungs including the collapsed regions (DSCs over 0.96.

Automatic segmentation of the glenohumeral cartilages from magnetic resonance images

International Nuclear Information System (INIS)

Neubert, A.; Yang, Z.; Engstrom, C.; Xia, Y.; Strudwick, M. W.; Chandra, S. S.; Crozier, S.; Fripp, J.

2016-01-01

Purpose: Magnetic resonance (MR) imaging plays a key role in investigating early degenerative disorders and traumatic injuries of the glenohumeral cartilages. Subtle morphometric and biochemical changes of potential relevance to clinical diagnosis, treatment planning, and evaluation can be assessed from measurements derived from in vivo MR segmentation of the cartilages. However, segmentation of the glenohumeral cartilages, using approaches spanning manual to automated methods, is technically challenging, due to their thin, curved structure and overlapping intensities of surrounding tissues. Automatic segmentation of the glenohumeral cartilages from MR imaging is not at the same level compared to the weight-bearing knee and hip joint cartilages despite the potential applications with respect to clinical investigation of shoulder disorders. In this work, the authors present a fully automated segmentation method for the glenohumeral cartilages using MR images of healthy shoulders. Methods: The method involves automated segmentation of the humerus and scapula bones using 3D active shape models, the extraction of the expected bone–cartilage interface, and cartilage segmentation using a graph-based method. The cartilage segmentation uses localization, patient specific tissue estimation, and a model of the cartilage thickness variation. The accuracy of this method was experimentally validated using a leave-one-out scheme on a database of MR images acquired from 44 asymptomatic subjects with a true fast imaging with steady state precession sequence on a 3 T scanner (Siemens Trio) using a dedicated shoulder coil. The automated results were compared to manual segmentations from two experts (an experienced radiographer and an experienced musculoskeletal anatomist) using the Dice similarity coefficient (DSC) and mean absolute surface distance (MASD) metrics. Results: Accurate and precise bone segmentations were achieved with mean DSC of 0.98 and 0.93 for the humeral head

Automatic segmentation of the glenohumeral cartilages from magnetic resonance images

Energy Technology Data Exchange (ETDEWEB)

Neubert, A., E-mail: ales.neubert@csiro.au [School of Information Technology and Electrical Engineering, University of Queensland, Brisbane 4072, Australia and The Australian E-Health Research Centre, CSIRO Health and Biosecurity, Brisbane 4029 (Australia); Yang, Z. [School of Information Technology and Electrical Engineering, University of Queensland, Brisbane 4072, Australia and Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190 (China); Engstrom, C. [School of Human Movement Studies, University of Queensland, Brisbane 4072 (Australia); Xia, Y.; Strudwick, M. W.; Chandra, S. S.; Crozier, S. [School of Information Technology and Electrical Engineering, University of Queensland, Brisbane 4072 (Australia); Fripp, J. [The Australian E-Health Research Centre, CSIRO Health and Biosecurity, Brisbane, 4029 (Australia)

2016-10-15

Purpose: Magnetic resonance (MR) imaging plays a key role in investigating early degenerative disorders and traumatic injuries of the glenohumeral cartilages. Subtle morphometric and biochemical changes of potential relevance to clinical diagnosis, treatment planning, and evaluation can be assessed from measurements derived from in vivo MR segmentation of the cartilages. However, segmentation of the glenohumeral cartilages, using approaches spanning manual to automated methods, is technically challenging, due to their thin, curved structure and overlapping intensities of surrounding tissues. Automatic segmentation of the glenohumeral cartilages from MR imaging is not at the same level compared to the weight-bearing knee and hip joint cartilages despite the potential applications with respect to clinical investigation of shoulder disorders. In this work, the authors present a fully automated segmentation method for the glenohumeral cartilages using MR images of healthy shoulders. Methods: The method involves automated segmentation of the humerus and scapula bones using 3D active shape models, the extraction of the expected bone–cartilage interface, and cartilage segmentation using a graph-based method. The cartilage segmentation uses localization, patient specific tissue estimation, and a model of the cartilage thickness variation. The accuracy of this method was experimentally validated using a leave-one-out scheme on a database of MR images acquired from 44 asymptomatic subjects with a true fast imaging with steady state precession sequence on a 3 T scanner (Siemens Trio) using a dedicated shoulder coil. The automated results were compared to manual segmentations from two experts (an experienced radiographer and an experienced musculoskeletal anatomist) using the Dice similarity coefficient (DSC) and mean absolute surface distance (MASD) metrics. Results: Accurate and precise bone segmentations were achieved with mean DSC of 0.98 and 0.93 for the humeral head

Image segmentation evaluation for very-large datasets

Science.gov (United States)

Reeves, Anthony P.; Liu, Shuang; Xie, Yiting

2016-03-01

With the advent of modern machine learning methods and fully automated image analysis there is a need for very large image datasets having documented segmentations for both computer algorithm training and evaluation. Current approaches of visual inspection and manual markings do not scale well to big data. We present a new approach that depends on fully automated algorithm outcomes for segmentation documentation, requires no manual marking, and provides quantitative evaluation for computer algorithms. The documentation of new image segmentations and new algorithm outcomes are achieved by visual inspection. The burden of visual inspection on large datasets is minimized by (a) customized visualizations for rapid review and (b) reducing the number of cases to be reviewed through analysis of quantitative segmentation evaluation. This method has been applied to a dataset of 7,440 whole-lung CT images for 6 different segmentation algorithms designed to fully automatically facilitate the measurement of a number of very important quantitative image biomarkers. The results indicate that we could achieve 93% to 99% successful segmentation for these algorithms on this relatively large image database. The presented evaluation method may be scaled to much larger image databases.

Spinal cord grey matter segmentation challenge.

Science.gov (United States)

Prados, Ferran; Ashburner, John; Blaiotta, Claudia; Brosch, Tom; Carballido-Gamio, Julio; Cardoso, Manuel Jorge; Conrad, Benjamin N; Datta, Esha; Dávid, Gergely; Leener, Benjamin De; Dupont, Sara M; Freund, Patrick; Wheeler-Kingshott, Claudia A M Gandini; Grussu, Francesco; Henry, Roland; Landman, Bennett A; Ljungberg, Emil; Lyttle, Bailey; Ourselin, Sebastien; Papinutto, Nico; Saporito, Salvatore; Schlaeger, Regina; Smith, Seth A; Summers, Paul; Tam, Roger; Yiannakas, Marios C; Zhu, Alyssa; Cohen-Adad, Julien

2017-05-15

An important image processing step in spinal cord magnetic resonance imaging is the ability to reliably and accurately segment grey and white matter for tissue specific analysis. There are several semi- or fully-automated segmentation methods for cervical cord cross-sectional area measurement with an excellent performance close or equal to the manual segmentation. However, grey matter segmentation is still challenging due to small cross-sectional size and shape, and active research is being conducted by several groups around the world in this field. Therefore a grey matter spinal cord segmentation challenge was organised to test different capabilities of various methods using the same multi-centre and multi-vendor dataset acquired with distinct 3D gradient-echo sequences. This challenge aimed to characterize the state-of-the-art in the field as well as identifying new opportunities for future improvements. Six different spinal cord grey matter segmentation methods developed independently by various research groups across the world and their performance were compared to manual segmentation outcomes, the present gold-standard. All algorithms provided good overall results for detecting the grey matter butterfly, albeit with variable performance in certain quality-of-segmentation metrics. The data have been made publicly available and the challenge web site remains open to new submissions. No modifications were introduced to any of the presented methods as a result of this challenge for the purposes of this publication. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Image segmentation of overlapping leaves based on Chan–Vese model and Sobel operator

Directory of Open Access Journals (Sweden)

Zhibin Wang

2018-03-01

Full Text Available To improve the segmentation precision of overlapping crop leaves, this paper presents an effective image segmentation method based on the Chan–Vese model and Sobel operator. The approach consists of three stages. First, a feature that identifies hues with relatively high levels of green is used to extract the region of leaves and remove the background. Second, the Chan–Vese model and improved Sobel operator are implemented to extract the leaf contours and detect the edges, respectively. Third, a target leaf with a complex background and overlapping is extracted by combining the results obtained by the Chan–Vese model and Sobel operator. To verify the effectiveness of the proposed algorithm, a segmentation experiment was performed on 30 images of cucumber leaf. The mean error rate of the proposed method is 0.0428, which is a decrease of 6.54% compared with the mean error rate of the level set method. Experimental results show that the proposed method can accurately extract the target leaf from cucumber leaf images with complex backgrounds and overlapping regions.

Operation of a Segmented Hall Thruster with Low-sputtering Carbon-velvet Electrodes

International Nuclear Information System (INIS)

Raitses, Y.; Staack, D.; Dunaevsky, A.; Fisch, N.J.

2005-01-01

Carbon fiber velvet material provides exceptional sputtering resistance properties exceeding those for graphite and carbon composite materials. A 2 kW Hall thruster with segmented electrodes made of this material was operated in the discharge voltage range of 200-700 V. The arcing between the floating velvet electrodes and the plasma was visually observed, especially, during the initial conditioning time, which lasted for about 1 h. The comparison of voltage versus current and plume characteristics of the Hall thruster with and without segmented electrodes indicates that the magnetic insulation of the segmented thruster improves with the discharge voltage at a fixed magnetic field. The observations reported here also extend the regimes wherein the segmented Hall thruster can have a narrower plume than that of the conventional nonsegmented thruster

Landfill gas operation and maintenance manual of practice

Energy Technology Data Exchange (ETDEWEB)

NONE

1997-03-01

This manual has the following objectives: (1) compile and present key portions of the general body of knowledge about operating and maintaining LFG control systems; (2) present information in an easy to understand format useful for hands-on practical use in the field; (3) present accepted practices and procedures for LFG control practices; (4) highlight key points, common mistakes and lessons learned from more than 20 years of industry experience, point out areas of controversy and indicate alternative practices where applicable; (5) compile key reference information; and (6) provide theory and discussion needed to develop a deeper understanding of LFG control and recovery.

Regional deep hyperthermia: impact of observer variability in CT-based manual tissue segmentation on simulated temperature distribution

Science.gov (United States)

Aklan, Bassim; Hartmann, Josefin; Zink, Diana; Siavooshhaghighi, Hadi; Merten, Ricarda; Putz, Florian; Ott, Oliver; Fietkau, Rainer; Bert, Christoph

2017-06-01

The aim of this study was to systematically investigate the influence of the inter- and intra-observer segmentation variation of tumors and organs at risk on the simulated temperature coverage of the target. CT scans of six patients with tumors in the pelvic region acquired for radiotherapy treatment planning were used for hyperthermia treatment planning. To study the effect of inter-observer variation, three observers manually segmented in the CT images of each patient the following structures: fat, muscle, bone and the bladder. The gross tumor volumes (GTV) were contoured by three radiation oncology residents and used as the hyperthermia target volumes. For intra-observer variation, one of the observers of each group contoured the structures of each patient three times with a time span of one week between the segmentations. Moreover, the impact of segmentation variations in organs at risk (OARs) between the three inter-observers was investigated on simulated temperature distributions using only one GTV. The spatial overlap between individual segmentations was assessed by the Dice similarity coefficient (DSC) and the mean surface distance (MSD). Additionally, the temperatures T90/T10 delivered to 90%/10% of the GTV, respectively, were assessed for each observer combination. The results of the segmentation similarity evaluation showed that the DSC of the inter-observer variation of fat, muscle, the bladder, bone and the target was 0.68  ±  0.12, 0.88  ±  0.05, 0.73  ±  0.14, 0.91  ±  0.04 and 0.64  ±  0.11, respectively. Similar results were found for the intra-observer variation. The MSD results were similar to the DSCs for both observer variations. A statistically significant difference (p  <  0.05) was found for T90 and T10 in the predicted target temperature due to the observer variability. The conclusion is that intra- and inter-observer variations have a significant impact on the temperature coverage of the

Operating manual for the emission spectrometer NOI-6e for laboratory use

International Nuclear Information System (INIS)

Albornoz G, M.P.

1993-08-01

This manual describes graphically and specifically how to operate the Emission Spectrometer NOI-6e. Detailed instructions are given for everything form turning on the equipment, quality control of several parameters, calibration, sample analysis; measurements and obtaining final results form the microprocessors. (author)

White matter hyperintensities segmentation: a new semi-automated method

Directory of Open Access Journals (Sweden)

Mariangela eIorio

2013-12-01

Full Text Available White matter hyperintensities (WMH are brain areas of increased signal on T2-weighted or fluid attenuated inverse recovery magnetic resonance imaging (MRI scans. In this study we present a new semi-automated method to measure WMH load that is based on the segmentation of the intensity histogram of fluid-attenuated inversion recovery images. Thirty patients with Mild Cognitive Impairment with variable WMH load were enrolled. The semi-automated WMH segmentation included: removal of non-brain tissue, spatial normalization, removal of cerebellum and brain stem, spatial filtering, thresholding to segment probable WMH, manual editing for correction of false positives and negatives, generation of WMH map and volumetric estimation of the WMH load. Accuracy was quantitatively evaluated by comparing semi-automated and manual WMH segmentations performed by two independent raters. Differences between the two procedures were assessed using Student’s t tests and similarity was evaluated using linear regression model and Dice Similarity Coefficient (DSC. The volumes of the manual and semi-automated segmentations did not statistically differ (t-value= -1.79, DF=29, p= 0.839 for rater 1; t-value= 1.113, DF=29, p= 0.2749 for rater 2, were highly correlated (R²= 0.921, F (1,29 =155,54, p

Fetal brain volumetry through MRI volumetric reconstruction and segmentation

Science.gov (United States)

Estroff, Judy A.; Barnewolt, Carol E.; Connolly, Susan A.; Warfield, Simon K.

2013-01-01

Purpose Fetal MRI volumetry is a useful technique but it is limited by a dependency upon motion-free scans, tedious manual segmentation, and spatial inaccuracy due to thick-slice scans. An image processing pipeline that addresses these limitations was developed and tested. Materials and methods The principal sequences acquired in fetal MRI clinical practice are multiple orthogonal single-shot fast spin echo scans. State-of-the-art image processing techniques were used for inter-slice motion correction and super-resolution reconstruction of high-resolution volumetric images from these scans. The reconstructed volume images were processed with intensity non-uniformity correction and the fetal brain extracted by using supervised automated segmentation. Results Reconstruction, segmentation and volumetry of the fetal brains for a cohort of twenty-five clinically acquired fetal MRI scans was done. Performance metrics for volume reconstruction, segmentation and volumetry were determined by comparing to manual tracings in five randomly chosen cases. Finally, analysis of the fetal brain and parenchymal volumes was performed based on the gestational age of the fetuses. Conclusion The image processing pipeline developed in this study enables volume rendering and accurate fetal brain volumetry by addressing the limitations of current volumetry techniques, which include dependency on motion-free scans, manual segmentation, and inaccurate thick-slice interpolation. PMID:20625848

Numerical simulation of manual operation at MID stand control room

International Nuclear Information System (INIS)

Doca, C.; Dobre, A.; Predescu, D.; Mielcioiu, A.

2003-01-01

Since 2000 at INR Pitesti a package of software products devoted to numerical simulation of manual operations at fueling machine control room was developed. So far, specified, designed, worked out and implemented was the PUPITRU code. The following issues were solved: graphical aspects of specific computer - human operator interface; functional and graphical simulation of the whole associated equipment of the control desk components; implementation of the main notation as used in the automated schemes of the control desk in view of the fast identification of the switches, lamps, instrumentation, etc.; implementation within PUPITRU code of the entire data base used in the frame of MID tests; implementation of a number of about 1000 numerical simulation equations describing specific operational MID testing situations

Manual airway labeling has limited reproducibility

DEFF Research Database (Denmark)

Petersen, Jens; Feragen, Aasa; Thomsen, Laura Hohwü

Purpose: Quantitative airway assessment is often performed in specific branches to enable comparison of measurements between patients and over time. Little is known on the accuracy in locating these branches. We determined inter- and intra-observer agreement of manual labeling of segmental bronch...... disagreement in expert labeling, possibly reflecting large anatomical heterogeneity and changes with inspiration. Consistent airway measurement cannot be guaranteed based on manual localization....

Operation Manual of the high voltage generator of the Pelletron electron accelerator; Manual de operacion del generador de alto voltaje del acelerador de electrones Pelletron

Energy Technology Data Exchange (ETDEWEB)

Hernandez M, V; Lopez V, H; Alba P, U

1988-04-15

The first version of a manual to operate the generator of high voltage generator of the Pelletron electron accelerator built in the ININ is presented. Since this generator has several components and/or elements, the one manual present has the purpose that the armed one or maintenance of anyone on its parts, is carried out in an orderly and efficient way. (Author)

Operator's Manual for SHEBA Powered Tether Balloon System

Science.gov (United States)

Lappen, Cara-Lyn; Randall, David A.

1998-01-01

The Surface Heat and Energy Budget of the Arctic (SHEBA) was an intensive field project which took place in the Arctic Ocean from October 1997 through October 1998. Its purpose was to measure as many facets of the Arctic environment as possible so that we would be able to better understand the interaction between the ice, atmosphere, and ocean and their interactions with global climate. One aspect of the atmospheric field component was launching tethered balloons to monitor the profiles of temperature, wind, pressure, and humidity, as well as examine the vertical structure of cloud droplet sizes and distributions. The tethered balloon that we used was one specially designed for use in freezing climates by SPEC Corporation in Boulder, Colorado. A special winch that was able to withstand Arctic temperature and weather became necessary when the testing of simple winch systems used in warmer climates failed under these extreme conditions. The purpose of this manual is to acquaint any new user to the powered tethered balloon system deployed at the The Surface Heat and Energy Budget of the Arctic (SHEBA ice camp. It includes a description of the preparations necessary to get ready for a launch, the mechanics of the actual launch, and an account of the proper procedure for taking down the equipment when finished. It will also include tips on how to minimize potential equipment failures, some trouble shooting, and some safety ideas. This manual is designed so that new operators can use the system with minimal previous training. At the end of this manual, the reader will find a quick checklist.

Reproducibility of myelin content-based human habenula segmentation at 3 Tesla.

Science.gov (United States)

Kim, Joo-Won; Naidich, Thomas P; Joseph, Joshmi; Nair, Divya; Glasser, Matthew F; O'halloran, Rafael; Doucet, Gaelle E; Lee, Won Hee; Krinsky, Hannah; Paulino, Alejandro; Glahn, David C; Anticevic, Alan; Frangou, Sophia; Xu, Junqian

2018-03-26

In vivo morphological study of the human habenula, a pair of small epithalamic nuclei adjacent to the dorsomedial thalamus, has recently gained significant interest for its role in reward and aversion processing. However, segmenting the habenula from in vivo magnetic resonance imaging (MRI) is challenging due to the habenula's small size and low anatomical contrast. Although manual and semi-automated habenula segmentation methods have been reported, the test-retest reproducibility of the segmented habenula volume and the consistency of the boundaries of habenula segmentation have not been investigated. In this study, we evaluated the intra- and inter-site reproducibility of in vivo human habenula segmentation from 3T MRI (0.7-0.8 mm isotropic resolution) using our previously proposed semi-automated myelin contrast-based method and its fully-automated version, as well as a previously published manual geometry-based method. The habenula segmentation using our semi-automated method showed consistent boundary definition (high Dice coefficient, low mean distance, and moderate Hausdorff distance) and reproducible volume measurement (low coefficient of variation). Furthermore, the habenula boundary in our semi-automated segmentation from 3T MRI agreed well with that in the manual segmentation from 7T MRI (0.5 mm isotropic resolution) of the same subjects. Overall, our proposed semi-automated habenula segmentation showed reliable and reproducible habenula localization, while its fully-automated version offers an efficient way for large sample analysis. © 2018 Wiley Periodicals, Inc.

SEGMENTATION AND CLASSIFICATION OF CERVICAL CYTOLOGY IMAGES USING MORPHOLOGICAL AND STATISTICAL OPERATIONS

Directory of Open Access Journals (Sweden)

S Anantha Sivaprakasam

2017-02-01

Full Text Available Cervical cancer that is a disease, in which malignant (cancer cells form in the tissues of the cervix, is one of the fourth leading causes of cancer death in female community worldwide. The cervical cancer can be prevented and/or cured if it is diagnosed in the pre-cancerous lesion stage or earlier. A common physical examination technique widely used in the screening is called Papanicolaou test or Pap test which is used to detect the abnormality of the cell. Due to intricacy of the cell nature, automating of this procedure is still a herculean task for the pathologist. This paper addresses solution for the challenges in terms of a simple and novel method to segment and classify the cervical cell automatically. The primary step of this procedure is pre-processing in which de-nosing, de-correlation operation and segregation of colour components are carried out, Then, two new techniques called Morphological and Statistical Edge based segmentation and Morphological and Statistical Region Based segmentation Techniques- put forward in this paper, and that are applied on the each component of image to segment the nuclei from cervical image. Finally, all segmented colour components are combined together to make a final segmentation result. After extracting the nuclei, the morphological features are extracted from the nuclei. The performance of two techniques mentioned above outperformed than standard segmentation techniques. Besides, Morphological and Statistical Edge based segmentation is outperformed than Morphological and Statistical Region based Segmentation. Finally, the nuclei are classified based on the morphological value The segmentation accuracy is echoed in classification accuracy. The overall segmentation accuracy is 97%.

The KAERI 10 MeV Electron Linac - Description and Operational Manual

Energy Technology Data Exchange (ETDEWEB)

Lee, Byung Cheol; Park, Seong Hee; Jung, Young Uk; Han, Young Hwan; Kang, Hee Young

2005-06-15

The objective of this technical report is to guide the right operation and maintenance of the KAERI electron linac system. The KAERI electron linac system consists of 2 MeV injector based on 176 MHz Normal conducting RF (Radio Frequency)cavity and 10 MeV main accelerator based on 352 MHz Superconducting RF cavity, electron beamlines (injection and extraction). Since a electron accelerator generates hazard radiation, this system is located at the shielded room in basement and we can operate the system using the remote control system. It includes the description and the operational manual as well as the detailed technical direction for trouble shooting.

The KAERI 10 MeV Electron Linac - Description and Operational Manual

International Nuclear Information System (INIS)

Lee, Byung Cheol; Park, Seong Hee; Jung, Young Uk; Han, Young Hwan; Kang, Hee Young

2005-06-01

The objective of this technical report is to guide the right operation and maintenance of the KAERI electron linac system. The KAERI electron linac system consists of 2 MeV injector based on 176 MHz Normal conducting RF (Radio Frequency)cavity and 10 MeV main accelerator based on 352 MHz Superconducting RF cavity, electron beamlines (injection and extraction). Since a electron accelerator generates hazard radiation, this system is located at the shielded room in basement and we can operate the system using the remote control system. It includes the description and the operational manual as well as the detailed technical direction for trouble shooting

Muscles of mastication model-based MR image segmentation

Energy Technology Data Exchange (ETDEWEB)

Ng, H.P. [NUS Graduate School for Integrative Sciences and Engineering, Singapore (Singapore); Agency for Science Technology and Research, Singapore (Singapore). Biomedical Imaging Lab.; Ong, S.H. [National Univ. of Singapore (Singapore). Dept. of Electrical and Computer Engineering; National Univ. of Singapore (Singapore). Div. of Bioengineering; Hu, Q.; Nowinski, W.L. [Agency for Science Technology and Research, Singapore (Singapore). Biomedical Imaging Lab.; Foong, K.W.C. [NUS Graduate School for Integrative Sciences and Engineering, Singapore (Singapore); National Univ. of Singapore (Singapore). Dept. of Preventive Dentistry; Goh, P.S. [National Univ. of Singapore (Singapore). Dept. of Diagnostic Radiology

2006-11-15

Objective: The muscles of mastication play a major role in the orodigestive system as the principal motive force for the mandible. An algorithm for segmenting these muscles from magnetic resonance (MR) images was developed and tested. Materials and methods: Anatomical information about the muscles of mastication in MR images is used to obtain the spatial relationships relating the muscle region of interest (ROI) and head ROI. A model-based technique that involves the spatial relationships between head and muscle ROIs as well as muscle templates is developed. In the segmentation stage, the muscle ROI is derived from the model. Within the muscle ROI, anisotropic diffusion is applied to smooth the texture, followed by thresholding to exclude bone and fat. The muscle template and morphological operators are employed to obtain an initial estimate of the muscle boundary, which then serves as the input contour to the gradient vector flow snake that iterates to the final segmentation. Results: The method was applied to segmentation of the masseter, lateral pterygoid and medial pterygoid in 75 images. The overlap indices (K) achieved are 91.4, 92.1 and 91.2%, respectively. Conclusion: A model-based method for segmenting the muscles of mastication from MR images was developed and tested. The results show good agreement between manual and automatic segmentations. (orig.)

Muscles of mastication model-based MR image segmentation

International Nuclear Information System (INIS)

Ng, H.P.; Agency for Science Technology and Research, Singapore; Ong, S.H.; National Univ. of Singapore; Hu, Q.; Nowinski, W.L.; Foong, K.W.C.; National Univ. of Singapore; Goh, P.S.

2006-01-01

Objective: The muscles of mastication play a major role in the orodigestive system as the principal motive force for the mandible. An algorithm for segmenting these muscles from magnetic resonance (MR) images was developed and tested. Materials and methods: Anatomical information about the muscles of mastication in MR images is used to obtain the spatial relationships relating the muscle region of interest (ROI) and head ROI. A model-based technique that involves the spatial relationships between head and muscle ROIs as well as muscle templates is developed. In the segmentation stage, the muscle ROI is derived from the model. Within the muscle ROI, anisotropic diffusion is applied to smooth the texture, followed by thresholding to exclude bone and fat. The muscle template and morphological operators are employed to obtain an initial estimate of the muscle boundary, which then serves as the input contour to the gradient vector flow snake that iterates to the final segmentation. Results: The method was applied to segmentation of the masseter, lateral pterygoid and medial pterygoid in 75 images. The overlap indices (K) achieved are 91.4, 92.1 and 91.2%, respectively. Conclusion: A model-based method for segmenting the muscles of mastication from MR images was developed and tested. The results show good agreement between manual and automatic segmentations. (orig.)

Development of a SCAT data management manual

International Nuclear Information System (INIS)

Lamarche, A.; Owens, E.H.

2005-01-01

The Shoreline Cleanup Assessment Technique (SCAT) is a commonly used method in North America to document oiling conditions in the aftermath of an oil spill. The data generated by SCAT can support all aspects of the process needed to develop and apply shoreline treatment methods such as planning treatment strategies, selecting treatment methods, providing detailed instructions to response personnel and evaluating the response effort. In order to be effective, SCAT data must be validated, entered within computerized systems, and transformed into support documents such as maps, tables and reports. This paper describes the development of a guidance manual for SCAT data coordinators and spill response managers that use the results of SCAT data. Guidance is presented for emergency procedures that enable the generation of minimal, but adequate, SCAT data management services. The creation of the manual involved the development of formal descriptions of the role, responsibilities and abilities of the SCAT data management team. The manual provides solution to several data processing issues, including those related to the presence of multiple parallel bands of oil within a segment of shoreline. Summary tables were created to report the length of oiled shoreline by oiling category and to present surface oiling characteristics in overview maps. The manual also includes details on how SCAT data is used for response planning, decision making and to support operations. 12 refs., 7 tabs., 8 figs

An objective evaluation framework for segmentation techniques of functional positron emission tomography studies

CERN Document Server

Kim, J; Eberl, S; Feng, D

2004-01-01

Segmentation of multi-dimensional functional positron emission tomography (PET) studies into regions of interest (ROI) exhibiting similar temporal behavior is useful in diagnosis and evaluation of neurological images. Quantitative evaluation plays a crucial role in measuring the segmentation algorithm's performance. Due to the lack of "ground truth" available for evaluating segmentation of clinical images, automated segmentation results are usually compared with manual delineation of structures which is, however, subjective, and is difficult to perform. Alternatively, segmentation of co-registered anatomical images such as magnetic resonance imaging (MRI) can be used as the ground truth to the PET segmentation. However, this is limited to PET studies which have corresponding MRI. In this study, we introduce a framework for the objective and quantitative evaluation of functional PET study segmentation without the need for manual delineation or registration to anatomical images of the patient. The segmentation ...

Deep Convolutional Neural Networks for Multi-Modality Isointense Infant Brain Image Segmentation

Science.gov (United States)

Zhang, Wenlu; Li, Rongjian; Deng, Houtao; Wang, Li; Lin, Weili; Ji, Shuiwang; Shen, Dinggang

2015-01-01

The segmentation of infant brain tissue images into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) plays an important role in studying early brain development in health and disease. In the isointense stage (approximately 6–8 months of age), WM and GM exhibit similar levels of intensity in both T1 and T2 MR images, making the tissue segmentation very challenging. Only a small number of existing methods have been designed for tissue segmentation in this isointense stage; however, they only used a single T1 or T2 images, or the combination of T1 and T2 images. In this paper, we propose to use deep convolutional neural networks (CNNs) for segmenting isointense stage brain tissues using multi-modality MR images. CNNs are a type of deep models in which trainable filters and local neighborhood pooling operations are applied alternatingly on the raw input images, resulting in a hierarchy of increasingly complex features. Specifically, we used multimodality information from T1, T2, and fractional anisotropy (FA) images as inputs and then generated the segmentation maps as outputs. The multiple intermediate layers applied convolution, pooling, normalization, and other operations to capture the highly nonlinear mappings between inputs and outputs. We compared the performance of our approach with that of the commonly used segmentation methods on a set of manually segmented isointense stage brain images. Results showed that our proposed model significantly outperformed prior methods on infant brain tissue segmentation. In addition, our results indicated that integration of multi-modality images led to significant performance improvement. PMID:25562829

Reproducible segmentation of white matter hyperintensities using a new statistical definition.

Science.gov (United States)

Damangir, Soheil; Westman, Eric; Simmons, Andrew; Vrenken, Hugo; Wahlund, Lars-Olof; Spulber, Gabriela

2017-06-01

We present a method based on a proposed statistical definition of white matter hyperintensities (WMH), which can work with any combination of conventional magnetic resonance (MR) sequences without depending on manually delineated samples. T1-weighted, T2-weighted, FLAIR, and PD sequences acquired at 1.5 Tesla from 119 subjects from the Kings Health Partners-Dementia Case Register (healthy controls, mild cognitive impairment, Alzheimer's disease) were used. The segmentation was performed using a proposed definition for WMH based on the one-tailed Kolmogorov-Smirnov test. The presented method was verified, given all possible combinations of input sequences, against manual segmentations and a high similarity (Dice 0.85-0.91) was observed. Comparing segmentations with different input sequences to one another also yielded a high similarity (Dice 0.83-0.94) that exceeded intra-rater similarity (Dice 0.75-0.91). We compared the results with those of other available methods and showed that the segmentation based on the proposed definition has better accuracy and reproducibility in the test dataset used. Overall, the presented definition is shown to produce accurate results with higher reproducibility than manual delineation. This approach can be an alternative to other manual or automatic methods not only because of its accuracy, but also due to its good reproducibility.

RRFC hardware operation manual

International Nuclear Information System (INIS)

Abhold, M.E.; Hsue, S.T.; Menlove, H.O.; Walton, G.

1996-05-01

The Research Reactor Fuel Counter (RRFC) system was developed to assay the 235 U content in spent Material Test Reactor (MTR) type fuel elements underwater in a spent fuel pool. RRFC assays the 235 U content using active neutron coincidence counting and also incorporates an ion chamber for gross gamma-ray measurements. This manual describes RRFC hardware, including detectors, electronics, and performance characteristics

Operations and Maintenance Manual for Expanded Bioventing System Site FC-2 Kelly AFB, Texas

National Research Council Canada - National Science Library

1996-01-01

This Operations and Maintenance Manual has been created as a guide for monitoring and maintaining the performance of the bioventing blower and vent well plumbing at the Fire Training Area (Site FC-2...

Robust automatic high resolution segmentation of SOFC anode porosity in 3D

DEFF Research Database (Denmark)

Jørgensen, Peter Stanley; Bowen, Jacob R.

2008-01-01

Routine use of 3D characterization of SOFCs by focused ion beam (FIB) serial sectioning is generally restricted by the time consuming task of manually delineating structures within each image slice. We apply advanced image analysis algorithms to automatically segment the porosity phase of an SOFC...... anode in 3D. The technique is based on numerical approximations to partial differential equations to evolve a 3D surface to the desired phase boundary. Vector fields derived from the experimentally acquired data are used as the driving force. The automatic segmentation compared to manual delineation...... reveals and good correspondence and the two approaches are quantitatively compared. It is concluded that the. automatic approach is more robust, more reproduceable and orders of magnitude quicker than manual segmentation of SOFC anode porosity for subsequent quantitative 3D analysis. Lastly...

Logistics and operations implications of manual control of spacecraft docking maneuvers

Science.gov (United States)

Brody, Adam R.; Ellis, Stephen R.

1991-01-01

The implications of logistics and operations on the manual control of spacecraft docking are discussed. The results of simulation studies to investigate fuel and time cost tradeoffs are reviewed and discussed. Comparisons of acceleration control and pulse control are presented to evaluate the effects of astronauts being instructed to use pulse mode for fuel conservation. The applications of the findings to moon and Mars missions are addressed.

Multiple Scale Music Segmentation Using Rhythm, Timbre, and Harmony

Directory of Open Access Journals (Sweden)

Kristoffer Jensen

2007-01-01

Full Text Available The segmentation of music into intro-chorus-verse-outro, and similar segments, is a difficult topic. A method for performing automatic segmentation based on features related to rhythm, timbre, and harmony is presented, and compared, between the features and between the features and manual segmentation of a database of 48 songs. Standard information retrieval performance measures are used in the comparison, and it is shown that the timbre-related feature performs best.

Automated MRI segmentation for individualized modeling of current flow in the human head.

Science.gov (United States)

Huang, Yu; Dmochowski, Jacek P; Su, Yuzhuo; Datta, Abhishek; Rorden, Christopher; Parra, Lucas C

2013-12-01

High-definition transcranial direct current stimulation (HD-tDCS) and high-density electroencephalography require accurate models of current flow for precise targeting and current source reconstruction. At a minimum, such modeling must capture the idiosyncratic anatomy of the brain, cerebrospinal fluid (CSF) and skull for each individual subject. Currently, the process to build such high-resolution individualized models from structural magnetic resonance images requires labor-intensive manual segmentation, even when utilizing available automated segmentation tools. Also, accurate placement of many high-density electrodes on an individual scalp is a tedious procedure. The goal was to develop fully automated techniques to reduce the manual effort in such a modeling process. A fully automated segmentation technique based on Statical Parametric Mapping 8, including an improved tissue probability map and an automated correction routine for segmentation errors, was developed, along with an automated electrode placement tool for high-density arrays. The performance of these automated routines was evaluated against results from manual segmentation on four healthy subjects and seven stroke patients. The criteria include segmentation accuracy, the difference of current flow distributions in resulting HD-tDCS models and the optimized current flow intensities on cortical targets. The segmentation tool can segment out not just the brain but also provide accurate results for CSF, skull and other soft tissues with a field of view extending to the neck. Compared to manual results, automated segmentation deviates by only 7% and 18% for normal and stroke subjects, respectively. The predicted electric fields in the brain deviate by 12% and 29% respectively, which is well within the variability observed for various modeling choices. Finally, optimized current flow intensities on cortical targets do not differ significantly. Fully automated individualized modeling may now be feasible

Automatic segmentation of myocardium at risk from contrast enhanced SSFP CMR: validation against expert readers and SPECT

International Nuclear Information System (INIS)

Tufvesson, Jane; Carlsson, Marcus; Aletras, Anthony H.; Engblom, Henrik; Deux, Jean-François; Koul, Sasha; Sörensson, Peder; Pernow, John; Atar, Dan; Erlinge, David; Arheden, Håkan; Heiberg, Einar

2016-01-01

Efficacy of reperfusion therapy can be assessed as myocardial salvage index (MSI) by determining the size of myocardium at risk (MaR) and myocardial infarction (MI), (MSI = 1-MI/MaR). Cardiovascular magnetic resonance (CMR) can be used to assess MI by late gadolinium enhancement (LGE) and MaR by either T2-weighted imaging or contrast enhanced SSFP (CE-SSFP). Automatic segmentation algorithms have been developed and validated for MI by LGE as well as for MaR by T2-weighted imaging. There are, however, no algorithms available for CE-SSFP. Therefore, the aim of this study was to develop and validate automatic segmentation of MaR in CE-SSFP. The automatic algorithm applies surface coil intensity correction and classifies myocardial intensities by Expectation Maximization to define a MaR region based on a priori regional criteria, and infarct region from LGE. Automatic segmentation was validated against manual delineation by expert readers in 183 patients with reperfused acute MI from two multi-center randomized clinical trials (RCT) (CHILL-MI and MITOCARE) and against myocardial perfusion SPECT in an additional set (n = 16). Endocardial and epicardial borders were manually delineated at end-diastole and end-systole. Manual delineation of MaR was used as reference and inter-observer variability was assessed for both manual delineation and automatic segmentation of MaR in a subset of patients (n = 15). MaR was expressed as percent of left ventricular mass (%LVM) and analyzed by bias (mean ± standard deviation). Regional agreement was analyzed by Dice Similarity Coefficient (DSC) (mean ± standard deviation). MaR assessed by manual and automatic segmentation were 36 ± 10 % and 37 ± 11 %LVM respectively with bias 1 ± 6 %LVM and regional agreement DSC 0.85 ± 0.08 (n = 183). MaR assessed by SPECT and CE-SSFP automatic segmentation were 27 ± 10 %LVM and 29 ± 7 %LVM respectively with bias 2 ± 7 %LVM. Inter-observer variability was 0 ± 3 %LVM for manual delineation and

Development of a Water Treatment Plant Operation Manual Using an Algorithmic Approach.

Science.gov (United States)

Counts, Cary A.

This document describes the steps to be followed in the development of a prescription manual for training of water treatment plant operators. Suggestions on how to prepare both flow and narrative prescriptions are provided for a variety of water treatment systems, including: raw water, flocculation, rapid sand filter, caustic soda feed, alum feed,…

Image enhancement software for underwater recovery operations: User's manual

Science.gov (United States)

Partridge, William J.; Therrien, Charles W.

1989-06-01

This report describes software for performing image enhancement on live or recorded video images. The software was developed for operational use during underwater recovery operations at the Naval Undersea Warfare Engineering Station. The image processing is performed on an IBM-PC/AT compatible computer equipped with hardware to digitize and display video images. The software provides the capability to provide contrast enhancement and other similar functions in real time through hardware lookup tables, to automatically perform histogram equalization, to capture one or more frames and average them or apply one of several different processing algorithms to a captured frame. The report is in the form of a user manual for the software and includes guided tutorial and reference sections. A Digital Image Processing Primer in the appendix serves to explain the principle concepts that are used in the image processing.

Upper airway segmentation and dimensions estimation from cone-beam CT image datasets

Energy Technology Data Exchange (ETDEWEB)

Shi, Hongjian; Scarfe, W.C. [Louisville Univ., KY (United States). School of Dentistry; Farman, A.G. [Louisville Univ., KY (United States). School of Dentistry; Louisville Univ., KY (United States). Div. of Radiology and Imaging Science

2006-11-15

Objective: To segment and measure the upper airway using cone-beam computed tomography (CBCT). This information may be useful as an imaging biomarker in the diagnostic assessment of patients with obstructive sleep apnea and in the planning of any necessary therapy. Methods: With Institutional Review Board Approval, anonymous CBCT datasets from subjects who had been imaged for a variety of conditions unrelated to the airway were evaluated. DICOM images were available. A segmentation algorithm was developed to separate the bounded upper airway and measurements were performed manually to determine the smallest cross-sectional area and the anteriorposterior distance of the retropalatal space (RP-SCA and RP-AP, respectively) and retroglossal space (RG-SCA and RG-AP, respectively). A segmentation algorithm was developed to separate the bounded upper airway and it was applied to determine RP-AP, RG-AP, the smallest transaxial-sectional area (TSCA) and largest sagittal view airway area (LCSA). A second algorithm was created to evaluate the airway volume within this bounded upper airway. Results: Measurements of the airway segmented automatically by the developed algorithm agreed with those obtained using manual segmentation. The corresponding volumes showed only very small differences considered clinically insignificant. Conclusion: Automatic segmentation of the airway imaged using CBCT is feasible and this method can be used to evaluate airway cross-section and volume comparable to measurements extracted using manual segmentation. (orig.)

Atlas-based automatic segmentation of head and neck organs at risk and nodal target volumes: a clinical validation

International Nuclear Information System (INIS)

Daisne, Jean-François; Blumhofer, Andreas

2013-01-01

Intensity modulated radiotherapy for head and neck cancer necessitates accurate definition of organs at risk (OAR) and clinical target volumes (CTV). This crucial step is time consuming and prone to inter- and intra-observer variations. Automatic segmentation by atlas deformable registration may help to reduce time and variations. We aim to test a new commercial atlas algorithm for automatic segmentation of OAR and CTV in both ideal and clinical conditions. The updated Brainlab automatic head and neck atlas segmentation was tested on 20 patients: 10 cN0-stages (ideal population) and 10 unselected N-stages (clinical population). Following manual delineation of OAR and CTV, automatic segmentation of the same set of structures was performed and afterwards manually corrected. Dice Similarity Coefficient (DSC), Average Surface Distance (ASD) and Maximal Surface Distance (MSD) were calculated for “manual to automatic” and “manual to corrected” volumes comparisons. In both groups, automatic segmentation saved about 40% of the corresponding manual segmentation time. This effect was more pronounced for OAR than for CTV. The edition of the automatically obtained contours significantly improved DSC, ASD and MSD. Large distortions of normal anatomy or lack of iodine contrast were the limiting factors. The updated Brainlab atlas-based automatic segmentation tool for head and neck Cancer patients is timesaving but still necessitates review and corrections by an expert

Atlas-based automatic segmentation of head and neck organs at risk and nodal target volumes: a clinical validation.

Science.gov (United States)

Daisne, Jean-François; Blumhofer, Andreas

2013-06-26

Intensity modulated radiotherapy for head and neck cancer necessitates accurate definition of organs at risk (OAR) and clinical target volumes (CTV). This crucial step is time consuming and prone to inter- and intra-observer variations. Automatic segmentation by atlas deformable registration may help to reduce time and variations. We aim to test a new commercial atlas algorithm for automatic segmentation of OAR and CTV in both ideal and clinical conditions. The updated Brainlab automatic head and neck atlas segmentation was tested on 20 patients: 10 cN0-stages (ideal population) and 10 unselected N-stages (clinical population). Following manual delineation of OAR and CTV, automatic segmentation of the same set of structures was performed and afterwards manually corrected. Dice Similarity Coefficient (DSC), Average Surface Distance (ASD) and Maximal Surface Distance (MSD) were calculated for "manual to automatic" and "manual to corrected" volumes comparisons. In both groups, automatic segmentation saved about 40% of the corresponding manual segmentation time. This effect was more pronounced for OAR than for CTV. The edition of the automatically obtained contours significantly improved DSC, ASD and MSD. Large distortions of normal anatomy or lack of iodine contrast were the limiting factors. The updated Brainlab atlas-based automatic segmentation tool for head and neck Cancer patients is timesaving but still necessitates review and corrections by an expert.

Integration of a browser based operator manual in the system environment of a process computer system; Integration eines browserbasierten Betriebshandbuchs in die Systemumgebung einer Prozessrechneranlage

Energy Technology Data Exchange (ETDEWEB)

Weber, Andreas [Westinghouse Electric Germany GmbH (Germany); Erfle, Robert [DOSCO GmbH, Heidelberg (Germany); Feinkohl, Dirk [E.ON Kernkraft GmbH (Germany). Kernkraftwerk Unterweser

2012-11-01

The integration of a browser based operator manual in the system environment of a process computer system is an optimization of the operating procedure in the control room and a safety enhancement due to faster and error-free access to the manual contents. Several requirements by the authorities have to be fulfilled: the operating manual has to be available as hard copy, the format has to be true to original, protection against manipulation has to be provided, the manual content of the browser-based version and the hard copy have to identical, and the display presentation has to be consistent with ergonomic principals. The integration of the on-line manual in the surveillance process computer system provides the operator with the relevant comments to the surveillance signal. The described integration of the on-line manual is an optimization of the operator's everyday job with respect to ergonomics and safety (human performance).

Generalized pixel profiling and comparative segmentation with application to arteriovenous malformation segmentation.

Science.gov (United States)

Babin, D; Pižurica, A; Bellens, R; De Bock, J; Shang, Y; Goossens, B; Vansteenkiste, E; Philips, W

2012-07-01

Extraction of structural and geometric information from 3-D images of blood vessels is a well known and widely addressed segmentation problem. The segmentation of cerebral blood vessels is of great importance in diagnostic and clinical applications, with a special application in diagnostics and surgery on arteriovenous malformations (AVM). However, the techniques addressing the problem of the AVM inner structure segmentation are rare. In this work we present a novel method of pixel profiling with the application to segmentation of the 3-D angiography AVM images. Our algorithm stands out in situations with low resolution images and high variability of pixel intensity. Another advantage of our method is that the parameters are set automatically, which yields little manual user intervention. The results on phantoms and real data demonstrate its effectiveness and potentials for fine delineation of AVM structure. Copyright © 2012 Elsevier B.V. All rights reserved.

Bone marrow cavity segmentation using graph-cuts with wavelet-based texture feature.

Science.gov (United States)

Shigeta, Hironori; Mashita, Tomohiro; Kikuta, Junichi; Seno, Shigeto; Takemura, Haruo; Ishii, Masaru; Matsuda, Hideo

2017-10-01

Emerging bioimaging technologies enable us to capture various dynamic cellular activities [Formula: see text]. As large amounts of data are obtained these days and it is becoming unrealistic to manually process massive number of images, automatic analysis methods are required. One of the issues for automatic image segmentation is that image-taking conditions are variable. Thus, commonly, many manual inputs are required according to each image. In this paper, we propose a bone marrow cavity (BMC) segmentation method for bone images as BMC is considered to be related to the mechanism of bone remodeling, osteoporosis, and so on. To reduce manual inputs to segment BMC, we classified the texture pattern using wavelet transformation and support vector machine. We also integrated the result of texture pattern classification into the graph-cuts-based image segmentation method because texture analysis does not consider spatial continuity. Our method is applicable to a particular frame in an image sequence in which the condition of fluorescent material is variable. In the experiment, we evaluated our method with nine types of mother wavelets and several sets of scale parameters. The proposed method with graph-cuts and texture pattern classification performs well without manual inputs by a user.

Manual for the GAW Precipitation Chemistry Programme: Guidelines, Data Quality Objectives and Standard Operating Procedures

National Research Council Canada - National Science Library

Allan, Mary A

2004-01-01

This is a manual for the Global Atmosphere Watch Precipitation Chemistry (GAW-PC) Programme. Where possible, it describes standard operating procedures and otherwise provides guidance on methods and procedures...

Generic method for automatic bladder segmentation on cone beam CT using a patient-specific bladder shape model

International Nuclear Information System (INIS)

Schoot, A. J. A. J. van de; Schooneveldt, G.; Wognum, S.; Stalpers, L. J. A.; Rasch, C. R. N.; Bel, A.; Hoogeman, M. S.; Chai, X.

2014-01-01

Purpose: The aim of this study is to develop and validate a generic method for automatic bladder segmentation on cone beam computed tomography (CBCT), independent of gender and treatment position (prone or supine), using only pretreatment imaging data. Methods: Data of 20 patients, treated for tumors in the pelvic region with the entire bladder visible on CT and CBCT, were divided into four equally sized groups based on gender and treatment position. The full and empty bladder contour, that can be acquired with pretreatment CT imaging, were used to generate a patient-specific bladder shape model. This model was used to guide the segmentation process on CBCT. To obtain the bladder segmentation, the reference bladder contour was deformed iteratively by maximizing the cross-correlation between directional grey value gradients over the reference and CBCT bladder edge. To overcome incorrect segmentations caused by CBCT image artifacts, automatic adaptations were implemented. Moreover, locally incorrect segmentations could be adapted manually. After each adapted segmentation, the bladder shape model was expanded and new shape patterns were calculated for following segmentations. All available CBCTs were used to validate the segmentation algorithm. The bladder segmentations were validated by comparison with the manual delineations and the segmentation performance was quantified using the Dice similarity coefficient (DSC), surface distance error (SDE) and SD of contour-to-contour distances. Also, bladder volumes obtained by manual delineations and segmentations were compared using a Bland-Altman error analysis. Results: The mean DSC, mean SDE, and mean SD of contour-to-contour distances between segmentations and manual delineations were 0.87, 0.27 cm and 0.22 cm (female, prone), 0.85, 0.28 cm and 0.22 cm (female, supine), 0.89, 0.21 cm and 0.17 cm (male, supine) and 0.88, 0.23 cm and 0.17 cm (male, prone), respectively. Manual local adaptations improved the segmentation

Semiautomatic segmentation of liver metastases on volumetric CT images

International Nuclear Information System (INIS)

Yan, Jiayong; Schwartz, Lawrence H.; Zhao, Binsheng

2015-01-01

Purpose: Accurate segmentation and quantification of liver metastases on CT images are critical to surgery/radiation treatment planning and therapy response assessment. To date, there are no reliable methods to perform such segmentation automatically. In this work, the authors present a method for semiautomatic delineation of liver metastases on contrast-enhanced volumetric CT images. Methods: The first step is to manually place a seed region-of-interest (ROI) in the lesion on an image. This ROI will (1) serve as an internal marker and (2) assist in automatically identifying an external marker. With these two markers, lesion contour on the image can be accurately delineated using traditional watershed transformation. Density information will then be extracted from the segmented 2D lesion and help determine the 3D connected object that is a candidate of the lesion volume. The authors have developed a robust strategy to automatically determine internal and external markers for marker-controlled watershed segmentation. By manually placing a seed region-of-interest in the lesion to be delineated on a reference image, the method can automatically determine dual threshold values to approximately separate the lesion from its surrounding structures and refine the thresholds from the segmented lesion for the accurate segmentation of the lesion volume. This method was applied to 69 liver metastases (1.1–10.3 cm in diameter) from a total of 15 patients. An independent radiologist manually delineated all lesions and the resultant lesion volumes served as the “gold standard” for validation of the method’s accuracy. Results: The algorithm received a median overlap, overestimation ratio, and underestimation ratio of 82.3%, 6.0%, and 11.5%, respectively, and a median average boundary distance of 1.2 mm. Conclusions: Preliminary results have shown that volumes of liver metastases on contrast-enhanced CT images can be accurately estimated by a semiautomatic segmentation

Automatic Cell Segmentation in Fluorescence Images of Confluent Cell Monolayers Using Multi-object Geometric Deformable Model.

Science.gov (United States)

Yang, Zhen; Bogovic, John A; Carass, Aaron; Ye, Mao; Searson, Peter C; Prince, Jerry L

2013-03-13

With the rapid development of microscopy for cell imaging, there is a strong and growing demand for image analysis software to quantitatively study cell morphology. Automatic cell segmentation is an important step in image analysis. Despite substantial progress, there is still a need to improve the accuracy, efficiency, and adaptability to different cell morphologies. In this paper, we propose a fully automatic method for segmenting cells in fluorescence images of confluent cell monolayers. This method addresses several challenges through a combination of ideas. 1) It realizes a fully automatic segmentation process by first detecting the cell nuclei as initial seeds and then using a multi-object geometric deformable model (MGDM) for final segmentation. 2) To deal with different defects in the fluorescence images, the cell junctions are enhanced by applying an order-statistic filter and principal curvature based image operator. 3) The final segmentation using MGDM promotes robust and accurate segmentation results, and guarantees no overlaps and gaps between neighboring cells. The automatic segmentation results are compared with manually delineated cells, and the average Dice coefficient over all distinguishable cells is 0.88.

Architectural study of the design and operation of advanced force feedback manual controllers

Science.gov (United States)

Tesar, Delbert; Kim, Whee-Kuk

1990-01-01

A teleoperator system consists of a manual controller, control hardware/software, and a remote manipulator. It was employed in either hazardous or unstructured, and/or remote environments. In teleoperation, the main-in-the-loop is the central concept that brings human intelligence to the teleoperator system. When teleoperation involves contact with an uncertain environment, providing the feeling of telepresence to the human operator is one of desired characteristics of the teleoperator system. Unfortunately, most available manual controllers in bilateral or force-reflecting teleoperator systems can be characterized by their bulky size, high costs, or lack of smoothness and transparency, and elementary architectures. To investigate other alternatives, a force-reflecting, 3 degree of freedom (dof) spherical manual controller is designed, analyzed, and implemented as a test bed demonstration in this research effort. To achieve an improved level of design to meet criteria such as compactness, portability, and a somewhat enhanced force-reflecting capability, the demonstration manual controller employs high gear-ratio reducers. To reduce the effects of the inertia and friction on the system, various force control strategies are applied and their performance investigated. The spherical manual controller uses a parallel geometry to minimize inertial and gravitational effects on its primary task of transparent information transfer. As an alternative to the spherical 3-dof manual controller, a new conceptual (or parallel) spherical 3-dof module is introduced with a full kinematic analysis. Also, the resulting kinematic properties are compared to those of other typical spherical 3-dof systems. The conceptual design of a parallel 6-dof manual controller and its kinematic analysis is presented. This 6-dof manual controller is similar to the Stewart Platform with the actuators located on the base to minimize the dynamic effects. Finally, a combination of the new 3-dof and 6-dof

Validation of clinical acceptability of an atlas-based segmentation algorithm for the delineation of organs at risk in head and neck cancer

Energy Technology Data Exchange (ETDEWEB)

Hoang Duc, Albert K., E-mail: albert.hoangduc.ucl@gmail.com; McClelland, Jamie; Modat, Marc; Cardoso, M. Jorge; Mendelson, Alex F. [Center for Medical Image Computing, University College London, London WC1E 6BT (United Kingdom); Eminowicz, Gemma; Mendes, Ruheena; Wong, Swee-Ling; D’Souza, Derek [Radiotherapy Department, University College London Hospitals, 235 Euston Road, London NW1 2BU (United Kingdom); Veiga, Catarina [Department of Medical Physics and Bioengineering, University College London, London WC1E 6BT (United Kingdom); Kadir, Timor [Mirada Medical UK, Oxford Center for Innovation, New Road, Oxford OX1 1BY (United Kingdom); Ourselin, Sebastien [Centre for Medical Image Computing, University College London, London WC1E 6BT (United Kingdom)

2015-09-15

Purpose: The aim of this study was to assess whether clinically acceptable segmentations of organs at risk (OARs) in head and neck cancer can be obtained automatically and efficiently using the novel “similarity and truth estimation for propagated segmentations” (STEPS) compared to the traditional “simultaneous truth and performance level estimation” (STAPLE) algorithm. Methods: First, 6 OARs were contoured by 2 radiation oncologists in a dataset of 100 patients with head and neck cancer on planning computed tomography images. Each image in the dataset was then automatically segmented with STAPLE and STEPS using those manual contours. Dice similarity coefficient (DSC) was then used to compare the accuracy of these automatic methods. Second, in a blind experiment, three separate and distinct trained physicians graded manual and automatic segmentations into one of the following three grades: clinically acceptable as determined by universal delineation guidelines (grade A), reasonably acceptable for clinical practice upon manual editing (grade B), and not acceptable (grade C). Finally, STEPS segmentations graded B were selected and one of the physicians manually edited them to grade A. Editing time was recorded. Results: Significant improvements in DSC can be seen when using the STEPS algorithm on large structures such as the brainstem, spinal canal, and left/right parotid compared to the STAPLE algorithm (all p < 0.001). In addition, across all three trained physicians, manual and STEPS segmentation grades were not significantly different for the brainstem, spinal canal, parotid (right/left), and optic chiasm (all p > 0.100). In contrast, STEPS segmentation grades were lower for the eyes (p < 0.001). Across all OARs and all physicians, STEPS produced segmentations graded as well as manual contouring at a rate of 83%, giving a lower bound on this rate of 80% with 95% confidence. Reduction in manual interaction time was on average 61% and 93% when automatic

Field Operations and Enforcement Manual for Air Pollution Control. Volume III: Inspection Procedures for Specific Industries.

Science.gov (United States)

Weisburd, Melvin I.

The Field Operations and Enforcement Manual for Air Pollution Control, Volume III, explains in detail the following: inspection procedures for specific sources, kraft pulp mills, animal rendering, steel mill furnaces, coking operations, petroleum refineries, chemical plants, non-ferrous smelting and refining, foundries, cement plants, aluminum…

Segmentation of 3D ultrasound computer tomography reflection images using edge detection and surface fitting

Science.gov (United States)

Hopp, T.; Zapf, M.; Ruiter, N. V.

2014-03-01

An essential processing step for comparison of Ultrasound Computer Tomography images to other modalities, as well as for the use in further image processing, is to segment the breast from the background. In this work we present a (semi-) automated 3D segmentation method which is based on the detection of the breast boundary in coronal slice images and a subsequent surface fitting. The method was evaluated using a software phantom and in-vivo data. The fully automatically processed phantom results showed that a segmentation of approx. 10% of the slices of a dataset is sufficient to recover the overall breast shape. Application to 16 in-vivo datasets was performed successfully using semi-automated processing, i.e. using a graphical user interface for manual corrections of the automated breast boundary detection. The processing time for the segmentation of an in-vivo dataset could be significantly reduced by a factor of four compared to a fully manual segmentation. Comparison to manually segmented images identified a smoother surface for the semi-automated segmentation with an average of 11% of differing voxels and an average surface deviation of 2mm. Limitations of the edge detection may be overcome by future updates of the KIT USCT system, allowing a fully-automated usage of our segmentation approach.

A semiautomatic CT-based ensemble segmentation of lung tumors: comparison with oncologists' delineations and with the surgical specimen.

Science.gov (United States)

Rios Velazquez, Emmanuel; Aerts, Hugo J W L; Gu, Yuhua; Goldgof, Dmitry B; De Ruysscher, Dirk; Dekker, Andre; Korn, René; Gillies, Robert J; Lambin, Philippe

2012-11-01

To assess the clinical relevance of a semiautomatic CT-based ensemble segmentation method, by comparing it to pathology and to CT/PET manual delineations by five independent radiation oncologists in non-small cell lung cancer (NSCLC). For 20 NSCLC patients (stages Ib-IIIb) the primary tumor was delineated manually on CT/PET scans by five independent radiation oncologists and segmented using a CT based semi-automatic tool. Tumor volume and overlap fractions between manual and semiautomatic-segmented volumes were compared. All measurements were correlated with the maximal diameter on macroscopic examination of the surgical specimen. Imaging data are available on www.cancerdata.org. High overlap fractions were observed between the semi-automatically segmented volumes and the intersection (92.5±9.0, mean±SD) and union (94.2±6.8) of the manual delineations. No statistically significant differences in tumor volume were observed between the semiautomatic segmentation (71.4±83.2 cm(3), mean±SD) and manual delineations (81.9±94.1 cm(3); p=0.57). The maximal tumor diameter of the semiautomatic-segmented tumor correlated strongly with the macroscopic diameter of the primary tumor (r=0.96). Semiautomatic segmentation of the primary tumor on CT demonstrated high agreement with CT/PET manual delineations and strongly correlated with the macroscopic diameter considered as the "gold standard". This method may be used routinely in clinical practice and could be employed as a starting point for treatment planning, target definition in multi-center clinical trials or for high throughput data mining research. This method is particularly suitable for peripherally located tumors. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Integrating atlas and graph cut methods for right ventricle blood-pool segmentation from cardiac cine MRI

Science.gov (United States)

Dangi, Shusil; Linte, Cristian A.

2017-03-01

Segmentation of right ventricle from cardiac MRI images can be used to build pre-operative anatomical heart models to precisely identify regions of interest during minimally invasive therapy. Furthermore, many functional parameters of right heart such as right ventricular volume, ejection fraction, myocardial mass and thickness can also be assessed from the segmented images. To obtain an accurate and computationally efficient segmentation of right ventricle from cardiac cine MRI, we propose a segmentation algorithm formulated as an energy minimization problem in a graph. Shape prior obtained by propagating label from an average atlas using affine registration is incorporated into the graph framework to overcome problems in ill-defined image regions. The optimal segmentation corresponding to the labeling with minimum energy configuration of the graph is obtained via graph-cuts and is iteratively refined to produce the final right ventricle blood pool segmentation. We quantitatively compare the segmentation results obtained from our algorithm to the provided gold-standard expert manual segmentation for 16 cine-MRI datasets available through the MICCAI 2012 Cardiac MR Right Ventricle Segmentation Challenge according to several similarity metrics, including Dice coefficient, Jaccard coefficient, Hausdorff distance, and Mean absolute distance error.

A comparative study of automatic image segmentation algorithms for target tracking in MR‐IGRT

Science.gov (United States)

Feng, Yuan; Kawrakow, Iwan; Olsen, Jeff; Parikh, Parag J.; Noel, Camille; Wooten, Omar; Du, Dongsu; Mutic, Sasa

2016-01-01

On‐board magnetic resonance (MR) image guidance during radiation therapy offers the potential for more accurate treatment delivery. To utilize the real‐time image information, a crucial prerequisite is the ability to successfully segment and track regions of interest (ROI). The purpose of this work is to evaluate the performance of different segmentation algorithms using motion images (4 frames per second) acquired using a MR image‐guided radiotherapy (MR‐IGRT) system. Manual contours of the kidney, bladder, duodenum, and a liver tumor by an experienced radiation oncologist were used as the ground truth for performance evaluation. Besides the manual segmentation, images were automatically segmented using thresholding, fuzzy k‐means (FKM), k‐harmonic means (KHM), and reaction‐diffusion level set evolution (RD‐LSE) algorithms, as well as the tissue tracking algorithm provided by the ViewRay treatment planning and delivery system (VR‐TPDS). The performance of the five algorithms was evaluated quantitatively by comparing with the manual segmentation using the Dice coefficient and target registration error (TRE) measured as the distance between the centroid of the manual ROI and the centroid of the automatically segmented ROI. All methods were able to successfully segment the bladder and the kidney, but only FKM, KHM, and VR‐TPDS were able to segment the liver tumor and the duodenum. The performance of the thresholding, FKM, KHM, and RD‐LSE algorithms degraded as the local image contrast decreased, whereas the performance of the VP‐TPDS method was nearly independent of local image contrast due to the reference registration algorithm. For segmenting high‐contrast images (i.e., kidney), the thresholding method provided the best speed (<1 ms) with a satisfying accuracy (Dice=0.95). When the image contrast was low, the VR‐TPDS method had the best automatic contour. Results suggest an image quality determination procedure before segmentation and

A comparative study of automatic image segmentation algorithms for target tracking in MR-IGRT.

Science.gov (United States)

Feng, Yuan; Kawrakow, Iwan; Olsen, Jeff; Parikh, Parag J; Noel, Camille; Wooten, Omar; Du, Dongsu; Mutic, Sasa; Hu, Yanle

2016-03-01

On-board magnetic resonance (MR) image guidance during radiation therapy offers the potential for more accurate treatment delivery. To utilize the real-time image information, a crucial prerequisite is the ability to successfully segment and track regions of interest (ROI). The purpose of this work is to evaluate the performance of different segmentation algorithms using motion images (4 frames per second) acquired using a MR image-guided radiotherapy (MR-IGRT) system. Manual contours of the kidney, bladder, duodenum, and a liver tumor by an experienced radiation oncologist were used as the ground truth for performance evaluation. Besides the manual segmentation, images were automatically segmented using thresholding, fuzzy k-means (FKM), k-harmonic means (KHM), and reaction-diffusion level set evolution (RD-LSE) algorithms, as well as the tissue tracking algorithm provided by the ViewRay treatment planning and delivery system (VR-TPDS). The performance of the five algorithms was evaluated quantitatively by comparing with the manual segmentation using the Dice coefficient and target registration error (TRE) measured as the distance between the centroid of the manual ROI and the centroid of the automatically segmented ROI. All methods were able to successfully segment the bladder and the kidney, but only FKM, KHM, and VR-TPDS were able to segment the liver tumor and the duodenum. The performance of the thresholding, FKM, KHM, and RD-LSE algorithms degraded as the local image contrast decreased, whereas the performance of the VP-TPDS method was nearly independent of local image contrast due to the reference registration algorithm. For segmenting high-contrast images (i.e., kidney), the thresholding method provided the best speed (<1 ms) with a satisfying accuracy (Dice=0.95). When the image contrast was low, the VR-TPDS method had the best automatic contour. Results suggest an image quality determination procedure before segmentation and a combination of different

Training manual for process operation and management of radioactive waste treatment facility

Energy Technology Data Exchange (ETDEWEB)

Shon, J. S.; Kim, K. J.; Ahn, S. J. [and others

2004-12-01

Radioactive Waste Treatment Facility (RWTF) has been operating for safe and effective treatment of radioactive wastes generated in the Korea Atomic Energy Research Institute (KAERI). In RWTF, there are evaporation, bituminization and solar evaporation processes for liquid waste, solid waste treatment process and laundry process. As other radioactive waste treatment facilities in foreign countries, the emergency situation such as fire and overflow of liquid waste can be taken place during the operation and result in the spread of contamination of radioactivity. So, easy and definite operating procedure is necessary for the safe operation of the facility. This manual can be available as easy and concise training materials for new employees and workers dispatched from service agency. Especially, in case of emergency urgently occurred during operation, everyone working in the facility can quickly stop the facility following this procedure.

Training manual for process operation and management of radioactive waste treatment facility

International Nuclear Information System (INIS)

Shon, J. S.; Kim, K. J.; Ahn, S. J.

2004-12-01

Radioactive Waste Treatment Facility (RWTF) has been operating for safe and effective treatment of radioactive wastes generated in the Korea Atomic Energy Research Institute (KAERI). In RWTF, there are evaporation, bituminization and solar evaporation processes for liquid waste, solid waste treatment process and laundry process. As other radioactive waste treatment facilities in foreign countries, the emergency situation such as fire and overflow of liquid waste can be taken place during the operation and result in the spread of contamination of radioactivity. So, easy and definite operating procedure is necessary for the safe operation of the facility. This manual can be available as easy and concise training materials for new employees and workers dispatched from service agency. Especially, in case of emergency urgently occurred during operation, everyone working in the facility can quickly stop the facility following this procedure

Delphi definition of the EADC-ADNI Harmonized Protocol for hippocampal segmentation on magnetic resonance.

Science.gov (United States)

Boccardi, Marina; Bocchetta, Martina; Apostolova, Liana G; Barnes, Josephine; Bartzokis, George; Corbetta, Gabriele; DeCarli, Charles; deToledo-Morrell, Leyla; Firbank, Michael; Ganzola, Rossana; Gerritsen, Lotte; Henneman, Wouter; Killiany, Ronald J; Malykhin, Nikolai; Pasqualetti, Patrizio; Pruessner, Jens C; Redolfi, Alberto; Robitaille, Nicolas; Soininen, Hilkka; Tolomeo, Daniele; Wang, Lei; Watson, Craig; Wolf, Henrike; Duvernoy, Henri; Duchesne, Simon; Jack, Clifford R; Frisoni, Giovanni B

2015-02-01

This study aimed to have international experts converge on a harmonized definition of whole hippocampus boundaries and segmentation procedures, to define standard operating procedures for magnetic resonance (MR)-based manual hippocampal segmentation. The panel received a questionnaire regarding whole hippocampus boundaries and segmentation procedures. Quantitative information was supplied to allow evidence-based answers. A recursive and anonymous Delphi procedure was used to achieve convergence. Significance of agreement among panelists was assessed by exact probability on Fisher's and binomial tests. Agreement was significant on the inclusion of alveus/fimbria (P = .021), whole hippocampal tail (P = .013), medial border of the body according to visible morphology (P = .0006), and on this combined set of features (P = .001). This definition captures 100% of hippocampal tissue, 100% of Alzheimer's disease-related atrophy, and demonstrated good reliability on preliminary intrarater (0.98) and inter-rater (0.94) estimates. Consensus was achieved among international experts with respect to hippocampal segmentation using MR resulting in a harmonized segmentation protocol. Copyright © 2015 The Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

A fully automated cell segmentation and morphometric parameter system for quantifying corneal endothelial cell morphology.

Science.gov (United States)

Al-Fahdawi, Shumoos; Qahwaji, Rami; Al-Waisy, Alaa S; Ipson, Stanley; Ferdousi, Maryam; Malik, Rayaz A; Brahma, Arun

2018-07-01

Corneal endothelial cell abnormalities may be associated with a number of corneal and systemic diseases. Damage to the endothelial cells can significantly affect corneal transparency by altering hydration of the corneal stroma, which can lead to irreversible endothelial cell pathology requiring corneal transplantation. To date, quantitative analysis of endothelial cell abnormalities has been manually performed by ophthalmologists using time consuming and highly subjective semi-automatic tools, which require an operator interaction. We developed and applied a fully-automated and real-time system, termed the Corneal Endothelium Analysis System (CEAS) for the segmentation and computation of endothelial cells in images of the human cornea obtained by in vivo corneal confocal microscopy. First, a Fast Fourier Transform (FFT) Band-pass filter is applied to reduce noise and enhance the image quality to make the cells more visible. Secondly, endothelial cell boundaries are detected using watershed transformations and Voronoi tessellations to accurately quantify the morphological parameters of the human corneal endothelial cells. The performance of the automated segmentation system was tested against manually traced ground-truth images based on a database consisting of 40 corneal confocal endothelial cell images in terms of segmentation accuracy and obtained clinical features. In addition, the robustness and efficiency of the proposed CEAS system were compared with manually obtained cell densities using a separate database of 40 images from controls (n = 11), obese subjects (n = 16) and patients with diabetes (n = 13). The Pearson correlation coefficient between automated and manual endothelial cell densities is 0.9 (p system, and the possibility of utilizing it in a real world clinical setting to enable rapid diagnosis and for patient follow-up, with an execution time of only 6 seconds per image. Copyright © 2018 Elsevier B.V. All rights reserved.

SU-E-J-224: Multimodality Segmentation of Head and Neck Tumors

International Nuclear Information System (INIS)

Aristophanous, M; Yang, J; Beadle, B

2014-01-01

Purpose: Develop an algorithm that is able to automatically segment tumor volume in Head and Neck cancer by integrating information from CT, PET and MR imaging simultaneously. Methods: Twenty three patients that were recruited under an adaptive radiotherapy protocol had MR, CT and PET/CT scans within 2 months prior to start of radiotherapy. The patients had unresectable disease and were treated either with chemoradiotherapy or radiation therapy alone. Using the Velocity software, the PET/CT and MR (T1 weighted+contrast) scans were registered to the planning CT using deformable and rigid registration respectively. The PET and MR images were then resampled according to the registration to match the planning CT. The resampled images, together with the planning CT, were fed into a multi-channel segmentation algorithm, which is based on Gaussian mixture models and solved with the expectation-maximization algorithm and Markov random fields. A rectangular region of interest (ROI) was manually placed to identify the tumor area and facilitate the segmentation process. The auto-segmented tumor contours were compared with the gross tumor volume (GTV) manually defined by the physician. The volume difference and Dice similarity coefficient (DSC) between the manual and autosegmented GTV contours were calculated as the quantitative evaluation metrics. Results: The multimodality segmentation algorithm was applied to all 23 patients. The volumes of the auto-segmented GTV ranged from 18.4cc to 32.8cc. The average (range) volume difference between the manual and auto-segmented GTV was −42% (−32.8%–63.8%). The average DSC value was 0.62, ranging from 0.39 to 0.78. Conclusion: An algorithm for the automated definition of tumor volume using multiple imaging modalities simultaneously was successfully developed and implemented for Head and Neck cancer. This development along with more accurate registration algorithms can aid physicians in the efforts to interpret the multitude of

SU-E-J-224: Multimodality Segmentation of Head and Neck Tumors

Energy Technology Data Exchange (ETDEWEB)

Aristophanous, M; Yang, J; Beadle, B [UT MD Anderson Cancer Center, Houston, TX (United States)

2014-06-01

Purpose: Develop an algorithm that is able to automatically segment tumor volume in Head and Neck cancer by integrating information from CT, PET and MR imaging simultaneously. Methods: Twenty three patients that were recruited under an adaptive radiotherapy protocol had MR, CT and PET/CT scans within 2 months prior to start of radiotherapy. The patients had unresectable disease and were treated either with chemoradiotherapy or radiation therapy alone. Using the Velocity software, the PET/CT and MR (T1 weighted+contrast) scans were registered to the planning CT using deformable and rigid registration respectively. The PET and MR images were then resampled according to the registration to match the planning CT. The resampled images, together with the planning CT, were fed into a multi-channel segmentation algorithm, which is based on Gaussian mixture models and solved with the expectation-maximization algorithm and Markov random fields. A rectangular region of interest (ROI) was manually placed to identify the tumor area and facilitate the segmentation process. The auto-segmented tumor contours were compared with the gross tumor volume (GTV) manually defined by the physician. The volume difference and Dice similarity coefficient (DSC) between the manual and autosegmented GTV contours were calculated as the quantitative evaluation metrics. Results: The multimodality segmentation algorithm was applied to all 23 patients. The volumes of the auto-segmented GTV ranged from 18.4cc to 32.8cc. The average (range) volume difference between the manual and auto-segmented GTV was −42% (−32.8%–63.8%). The average DSC value was 0.62, ranging from 0.39 to 0.78. Conclusion: An algorithm for the automated definition of tumor volume using multiple imaging modalities simultaneously was successfully developed and implemented for Head and Neck cancer. This development along with more accurate registration algorithms can aid physicians in the efforts to interpret the multitude of

Hydrophobic coating of microfluidic chips structured by SU-8 polymer for segmented flow operation

International Nuclear Information System (INIS)

Schumacher, J T; Grodrian, A; Metze, J; Kremin, C; Hoffmann, M

2008-01-01

We present a hydrophobization procedure for SU-8-based microfluidic chips on borofloat substrates. Different layouts of gold electrodes passivated by the polymer have been investigated. The chips are used for segmented flow in a two-fluid mode that requires a distinct hydrophobicity of the channel walls which is generated by the use of specific silane. In this paper we describe the production and silanization of the chips and demonstrate segmented flow operation

Cerebrovascular plaque segmentation using object class uncertainty snake in MR images

Science.gov (United States)

Das, Bipul; Saha, Punam K.; Wolf, Ronald; Song, Hee Kwon; Wright, Alexander C.; Wehrli, Felix W.

2005-04-01

exceptionally well with manual segmentation completed by radiology experts. Reproducibility of the proposed method is estimated for both intra- and inter-operator studies.

TED: A Tolerant Edit Distance for segmentation evaluation.

Science.gov (United States)

Funke, Jan; Klein, Jonas; Moreno-Noguer, Francesc; Cardona, Albert; Cook, Matthew

2017-02-15

In this paper, we present a novel error measure to compare a computer-generated segmentation of images or volumes against ground truth. This measure, which we call Tolerant Edit Distance (TED), is motivated by two observations that we usually encounter in biomedical image processing: (1) Some errors, like small boundary shifts, are tolerable in practice. Which errors are tolerable is application dependent and should be explicitly expressible in the measure. (2) Non-tolerable errors have to be corrected manually. The effort needed to do so should be reflected by the error measure. Our measure is the minimal weighted sum of split and merge operations to apply to one segmentation such that it resembles another segmentation within specified tolerance bounds. This is in contrast to other commonly used measures like Rand index or variation of information, which integrate small, but tolerable, differences. Additionally, the TED provides intuitive numbers and allows the localization and classification of errors in images or volumes. We demonstrate the applicability of the TED on 3D segmentations of neurons in electron microscopy images where topological correctness is arguable more important than exact boundary locations. Furthermore, we show that the TED is not just limited to evaluation tasks. We use it as the loss function in a max-margin learning framework to find parameters of an automatic neuron segmentation algorithm. We show that training to minimize the TED, i.e., to minimize crucial errors, leads to higher segmentation accuracy compared to other learning methods. Copyright © 2016. Published by Elsevier Inc.

Automated CT-based segmentation and quantification of total intracranial volume

Energy Technology Data Exchange (ETDEWEB)

Aguilar, Carlos; Wahlund, Lars-Olof; Westman, Eric [Karolinska Institute, Department of Neurobiology, Care Sciences and Society (NVS), Division of Clinical Geriatrics, Stockholm (Sweden); Edholm, Kaijsa; Cavallin, Lena; Muller, Susanne; Axelsson, Rimma [Karolinska Institute, Department of Clinical Science, Intervention and Technology, Division of Medical Imaging and Technology, Stockholm (Sweden); Karolinska University Hospital in Huddinge, Department of Radiology, Stockholm (Sweden); Simmons, Andrew [King' s College London, Institute of Psychiatry, London (United Kingdom); NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia, London (United Kingdom); Skoog, Ingmar [Gothenburg University, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy, Gothenburg (Sweden); Larsson, Elna-Marie [Uppsala University, Department of Surgical Sciences, Radiology, Akademiska Sjukhuset, Uppsala (Sweden)

2015-11-15

To develop an algorithm to segment and obtain an estimate of total intracranial volume (tICV) from computed tomography (CT) images. Thirty-six CT examinations from 18 patients were included. Ten patients were examined twice the same day and eight patients twice six months apart (these patients also underwent MRI). The algorithm combines morphological operations, intensity thresholding and mixture modelling. The method was validated against manual delineation and its robustness assessed from repeated imaging examinations. Using automated MRI software, the comparability with MRI was investigated. Volumes were compared based on average relative volume differences and their magnitudes; agreement was shown by a Bland-Altman analysis graph. We observed good agreement between our algorithm and manual delineation of a trained radiologist: the Pearson's correlation coefficient was r = 0.94, tICVml[manual] = 1.05 x tICVml[automated] - 33.78 (R{sup 2} = 0.88). Bland-Altman analysis showed a bias of 31 mL and a standard deviation of 30 mL over a range of 1265 to 1526 mL. tICV measurements derived from CT using our proposed algorithm have shown to be reliable and consistent compared to manual delineation. However, it appears difficult to directly compare tICV measures between CT and MRI. (orig.)

Automated CT-based segmentation and quantification of total intracranial volume

International Nuclear Information System (INIS)

Aguilar, Carlos; Wahlund, Lars-Olof; Westman, Eric; Edholm, Kaijsa; Cavallin, Lena; Muller, Susanne; Axelsson, Rimma; Simmons, Andrew; Skoog, Ingmar; Larsson, Elna-Marie

2015-01-01

To develop an algorithm to segment and obtain an estimate of total intracranial volume (tICV) from computed tomography (CT) images. Thirty-six CT examinations from 18 patients were included. Ten patients were examined twice the same day and eight patients twice six months apart (these patients also underwent MRI). The algorithm combines morphological operations, intensity thresholding and mixture modelling. The method was validated against manual delineation and its robustness assessed from repeated imaging examinations. Using automated MRI software, the comparability with MRI was investigated. Volumes were compared based on average relative volume differences and their magnitudes; agreement was shown by a Bland-Altman analysis graph. We observed good agreement between our algorithm and manual delineation of a trained radiologist: the Pearson's correlation coefficient was r = 0.94, tICVml[manual] = 1.05 x tICVml[automated] - 33.78 (R 2 = 0.88). Bland-Altman analysis showed a bias of 31 mL and a standard deviation of 30 mL over a range of 1265 to 1526 mL. tICV measurements derived from CT using our proposed algorithm have shown to be reliable and consistent compared to manual delineation. However, it appears difficult to directly compare tICV measures between CT and MRI. (orig.)

Quantifying brain tissue volume in multiple sclerosis with automated lesion segmentation and filling

Directory of Open Access Journals (Sweden)

Sergi Valverde

2015-01-01

Full Text Available Lesion filling has been successfully applied to reduce the effect of hypo-intense T1-w Multiple Sclerosis (MS lesions on automatic brain tissue segmentation. However, a study of fully automated pipelines incorporating lesion segmentation and lesion filling on tissue volume analysis has not yet been performed. Here, we analyzed the % of error introduced by automating the lesion segmentation and filling processes in the tissue segmentation of 70 clinically isolated syndrome patient images. First of all, images were processed using the LST and SLS toolkits with different pipeline combinations that differed in either automated or manual lesion segmentation, and lesion filling or masking out lesions. Then, images processed following each of the pipelines were segmented into gray matter (GM and white matter (WM using SPM8, and compared with the same images where expert lesion annotations were filled before segmentation. Our results showed that fully automated lesion segmentation and filling pipelines reduced significantly the % of error in GM and WM volume on images of MS patients, and performed similarly to the images where expert lesion annotations were masked before segmentation. In all the pipelines, the amount of misclassified lesion voxels was the main cause in the observed error in GM and WM volume. However, the % of error was significantly lower when automatically estimated lesions were filled and not masked before segmentation. These results are relevant and suggest that LST and SLS toolboxes allow the performance of accurate brain tissue volume measurements without any kind of manual intervention, which can be convenient not only in terms of time and economic costs, but also to avoid the inherent intra/inter variability between manual annotations.

Functional segmentation of dynamic PET studies: Open source implementation and validation of a leader-follower-based algorithm.

Science.gov (United States)

Mateos-Pérez, José María; Soto-Montenegro, María Luisa; Peña-Zalbidea, Santiago; Desco, Manuel; Vaquero, Juan José

2016-02-01

We present a novel segmentation algorithm for dynamic PET studies that groups pixels according to the similarity of their time-activity curves. Sixteen mice bearing a human tumor cell line xenograft (CH-157MN) were imaged with three different (68)Ga-DOTA-peptides (DOTANOC, DOTATATE, DOTATOC) using a small animal PET-CT scanner. Regional activities (input function and tumor) were obtained after manual delineation of regions of interest over the image. The algorithm was implemented under the jClustering framework and used to extract the same regional activities as in the manual approach. The volume of distribution in the tumor was computed using the Logan linear method. A Kruskal-Wallis test was used to investigate significant differences between the manually and automatically obtained volumes of distribution. The algorithm successfully segmented all the studies. No significant differences were found for the same tracer across different segmentation methods. Manual delineation revealed significant differences between DOTANOC and the other two tracers (DOTANOC - DOTATATE, p=0.020; DOTANOC - DOTATOC, p=0.033). Similar differences were found using the leader-follower algorithm. An open implementation of a novel segmentation method for dynamic PET studies is presented and validated in rodent studies. It successfully replicated the manual results obtained in small-animal studies, thus making it a reliable substitute for this task and, potentially, for other dynamic segmentation procedures. Copyright © 2016 Elsevier Ltd. All rights reserved.

Automated segmentation of tumors on bone scans using anatomy-specific thresholding

Science.gov (United States)

Chu, Gregory H.; Lo, Pechin; Kim, Hyun J.; Lu, Peiyun; Ramakrishna, Bharath; Gjertson, David; Poon, Cheryce; Auerbach, Martin; Goldin, Jonathan; Brown, Matthew S.

2012-03-01

Quantification of overall tumor area on bone scans may be a potential biomarker for treatment response assessment and has, to date, not been investigated. Segmentation of bone metastases on bone scans is a fundamental step for this response marker. In this paper, we propose a fully automated computerized method for the segmentation of bone metastases on bone scans, taking into account characteristics of different anatomic regions. A scan is first segmented into anatomic regions via an atlas-based segmentation procedure, which involves non-rigidly registering a labeled atlas scan to the patient scan. Next, an intensity normalization method is applied to account for varying levels of radiotracer dosing levels and scan timing. Lastly, lesions are segmented via anatomic regionspecific intensity thresholding. Thresholds are chosen by receiver operating characteristic (ROC) curve analysis against manual contouring by board certified nuclear medicine physicians. A leave-one-out cross validation of our method on a set of 39 bone scans with metastases marked by 2 board-certified nuclear medicine physicians yielded a median sensitivity of 95.5%, and specificity of 93.9%. Our method was compared with a global intensity thresholding method. The results show a comparable sensitivity and significantly improved overall specificity, with a p-value of 0.0069.

Automatic tissue image segmentation based on image processing and deep learning

Science.gov (United States)

Kong, Zhenglun; Luo, Junyi; Xu, Shengpu; Li, Ting

2018-02-01

Image segmentation plays an important role in multimodality imaging, especially in fusion structural images offered by CT, MRI with functional images collected by optical technologies or other novel imaging technologies. Plus, image segmentation also provides detailed structure description for quantitative visualization of treating light distribution in the human body when incorporated with 3D light transport simulation method. Here we used image enhancement, operators, and morphometry methods to extract the accurate contours of different tissues such as skull, cerebrospinal fluid (CSF), grey matter (GM) and white matter (WM) on 5 fMRI head image datasets. Then we utilized convolutional neural network to realize automatic segmentation of images in a deep learning way. We also introduced parallel computing. Such approaches greatly reduced the processing time compared to manual and semi-automatic segmentation and is of great importance in improving speed and accuracy as more and more samples being learned. Our results can be used as a criteria when diagnosing diseases such as cerebral atrophy, which is caused by pathological changes in gray matter or white matter. We demonstrated the great potential of such image processing and deep leaning combined automatic tissue image segmentation in personalized medicine, especially in monitoring, and treatments.

Segmentation of the temporalis muscle from MR data

Energy Technology Data Exchange (ETDEWEB)

Ng, H.P. [NUS Graduate School for Integrative Sciences and Engineering, Singapore (Singapore); Agency for Science Technology and Research, Biomedical Imaging Lab, Singapore (Singapore); Hu, Q.M.; Liu, J.; Nowinski, W.L. [Agency for Science Technology and Research, Biomedical Imaging Lab, Singapore (Singapore); Ong, S.H. [National University of Singapore, Department of Electrical and Computer Engineering, Singapore (Singapore); National University of Singapore, Division of Bioengineering, Singapore (Singapore); Foong, K.W.C. [NUS Graduate School for Integrative Sciences and Engineering, Singapore (Singapore); National University of Singapore, Department of Preventive Dentistry, Singapore (Singapore); Goh, P.S. [National University of Singapore, Department of Diagnostic Radiology, Singapore (Singapore)

2007-06-15

Objective A method for segmenting the temporalis from magnetic resonance (MR) images was developed and tested. The temporalis muscle is one of the muscles of mastication which plays a major role in the mastication system. Materials and methods The temporalis region of interest (ROI) and the head ROI are defined in reference images, from which the spatial relationship between the two ROIs is derived. This relationship is used to define the temporalis ROI in a study image. Range-constrained thresholding is then employed to remove the fat, bone marrow and muscle tendon in the ROI. Adaptive morphological operations are then applied to first remove the brain tissue, followed by the removal of the other soft tissues surrounding the temporalis. Ten adult head MR data sets were processed to test this method. Results Using five data sets each for training and testing, the method was applied to the segmentation of the temporalis in 25 MR images (five from each test set). An average overlap index ({kappa}) of 90.2% was obtained. Applying a leave-one-out evaluation method, an average {kappa} of 90.5% was obtained from 50 test images. Conclusion A method for segmenting the temporalis from MR images was developed and tested on in vivo data sets. The results show that there is consistency between manual and automatic segmentations. (orig.)

Segmentation of the temporalis muscle from MR data

International Nuclear Information System (INIS)

Ng, H.P.; Hu, Q.M.; Liu, J.; Nowinski, W.L.; Ong, S.H.; Foong, K.W.C.; Goh, P.S.

2007-01-01

Objective A method for segmenting the temporalis from magnetic resonance (MR) images was developed and tested. The temporalis muscle is one of the muscles of mastication which plays a major role in the mastication system. Materials and methods The temporalis region of interest (ROI) and the head ROI are defined in reference images, from which the spatial relationship between the two ROIs is derived. This relationship is used to define the temporalis ROI in a study image. Range-constrained thresholding is then employed to remove the fat, bone marrow and muscle tendon in the ROI. Adaptive morphological operations are then applied to first remove the brain tissue, followed by the removal of the other soft tissues surrounding the temporalis. Ten adult head MR data sets were processed to test this method. Results Using five data sets each for training and testing, the method was applied to the segmentation of the temporalis in 25 MR images (five from each test set). An average overlap index (κ) of 90.2% was obtained. Applying a leave-one-out evaluation method, an average κ of 90.5% was obtained from 50 test images. Conclusion A method for segmenting the temporalis from MR images was developed and tested on in vivo data sets. The results show that there is consistency between manual and automatic segmentations. (orig.)

Superiority Of Graph-Based Visual Saliency GVS Over Other Image Segmentation Methods

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Umu Lamboi

2017-02-01

Full Text Available Although inherently tedious the segmentation of images and the evaluation of segmented images are critical in computer vision processes. One of the main challenges in image segmentation evaluation arises from the basic conflict between generality and objectivity. For general segmentation purposes the lack of well-defined ground-truth and segmentation accuracy limits the evaluation of specific applications. Subjectivity is the most common method of evaluation of segmentation quality where segmented images are visually compared. This is daunting task however limits the scope of segmentation evaluation to a few predetermined sets of images. As an alternative supervised evaluation compares segmented images against manually-segmented or pre-processed benchmark images. Not only good evaluation methods allow for different comparisons but also for integration with target recognition systems for adaptive selection of appropriate segmentation granularity with improved recognition accuracy. Most of the current segmentation methods still lack satisfactory measures of effectiveness. Thus this study proposed a supervised framework which uses visual saliency detection to quantitatively evaluate image segmentation quality. The new benchmark evaluator uses Graph-based Visual Saliency GVS to compare boundary outputs for manually segmented images. Using the Berkeley Segmentation Database the proposed algorithm was tested against 4 other quantitative evaluation methods Probabilistic Rand Index PRI Variation of Information VOI Global Consistency Error GSE and Boundary Detection Error BDE. Based on the results the GVS approach outperformed any of the other 4 independent standard methods in terms of visual saliency detection of images.

Semi-automated segmentation of a glioblastoma multiforme on brain MR images for radiotherapy planning.

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Hori, Daisuke; Katsuragawa, Shigehiko; Murakami, Ryuuji; Hirai, Toshinori

2010-04-20

We propose a computerized method for semi-automated segmentation of the gross tumor volume (GTV) of a glioblastoma multiforme (GBM) on brain MR images for radiotherapy planning (RTP). Three-dimensional (3D) MR images of 28 cases with a GBM were used in this study. First, a sphere volume of interest (VOI) including the GBM was selected by clicking a part of the GBM region in the 3D image. Then, the sphere VOI was transformed to a two-dimensional (2D) image by use of a spiral-scanning technique. We employed active contour models (ACM) to delineate an optimal outline of the GBM in the transformed 2D image. After inverse transform of the optimal outline to the 3D space, a morphological filter was applied to smooth the shape of the 3D segmented region. For evaluation of our computerized method, we compared the computer output with manually segmented regions, which were obtained by a therapeutic radiologist using a manual tracking method. In evaluating our segmentation method, we employed the Jaccard similarity coefficient (JSC) and the true segmentation coefficient (TSC) in volumes between the computer output and the manually segmented region. The mean and standard deviation of JSC and TSC were 74.2+/-9.8% and 84.1+/-7.1%, respectively. Our segmentation method provided a relatively accurate outline for GBM and would be useful for radiotherapy planning.

Application of a semi-automatic cartilage segmentation method for biomechanical modeling of the knee joint.

Science.gov (United States)

Liukkonen, Mimmi K; Mononen, Mika E; Tanska, Petri; Saarakkala, Simo; Nieminen, Miika T; Korhonen, Rami K

2017-10-01

Manual segmentation of articular cartilage from knee joint 3D magnetic resonance images (MRI) is a time consuming and laborious task. Thus, automatic methods are needed for faster and reproducible segmentations. In the present study, we developed a semi-automatic segmentation method based on radial intensity profiles to generate 3D geometries of knee joint cartilage which were then used in computational biomechanical models of the knee joint. Six healthy volunteers were imaged with a 3T MRI device and their knee cartilages were segmented both manually and semi-automatically. The values of cartilage thicknesses and volumes produced by these two methods were compared. Furthermore, the influences of possible geometrical differences on cartilage stresses and strains in the knee were evaluated with finite element modeling. The semi-automatic segmentation and 3D geometry construction of one knee joint (menisci, femoral and tibial cartilages) was approximately two times faster than with manual segmentation. Differences in cartilage thicknesses, volumes, contact pressures, stresses, and strains between segmentation methods in femoral and tibial cartilage were mostly insignificant (p > 0.05) and random, i.e. there were no systematic differences between the methods. In conclusion, the devised semi-automatic segmentation method is a quick and accurate way to determine cartilage geometries; it may become a valuable tool for biomechanical modeling applications with large patient groups.

A Semiautomatic Segmentation Algorithm for Extracting the Complete Structure of Acini from Synchrotron Micro-CT Images

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Luosha Xiao

2013-01-01

Full Text Available Pulmonary acinus is the largest airway unit provided with alveoli where blood/gas exchange takes place. Understanding the complete structure of acinus is necessary to measure the pathway of gas exchange and to simulate various mechanical phenomena in the lungs. The usual manual segmentation of a complete acinus structure from their experimentally obtained images is difficult and extremely time-consuming, which hampers the statistical analysis. In this study, we develop a semiautomatic segmentation algorithm for extracting the complete structure of acinus from synchrotron micro-CT images of the closed chest of mouse lungs. The algorithm uses a combination of conventional binary image processing techniques based on the multiscale and hierarchical nature of lung structures. Specifically, larger structures are removed, while smaller structures are isolated from the image by repeatedly applying erosion and dilation operators in order, adjusting the parameter referencing to previously obtained morphometric data. A cluster of isolated acini belonging to the same terminal bronchiole is obtained without floating voxels. The extracted acinar models above 98% agree well with those extracted manually. The run time is drastically shortened compared with manual methods. These findings suggest that our method may be useful for taking samples used in the statistical analysis of acinus.

Graphic Arts--Offset Press Operator/Duplicating Machine. TI-622. Instructor's Manual and Student Learning Activity Guide.

Science.gov (United States)

Michelsen, Robert F.

This instructor's manual and student learning activity guide comprise a kit for a graphic arts activity on offset press operator/duplicating machine. Purpose stated for the activity is to provide the student with an understanding of the basic operation involved in the production of printed matter in the graphic communications industry through the…

MIA-Clustering: a novel method for segmentation of paleontological material

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Christopher J. Dunmore

2018-02-01

Full Text Available Paleontological research increasingly uses high-resolution micro-computed tomography (μCT to study the inner architecture of modern and fossil bone material to answer important questions regarding vertebrate evolution. This non-destructive method allows for the measurement of otherwise inaccessible morphology. Digital measurement is predicated on the accurate segmentation of modern or fossilized bone from other structures imaged in μCT scans, as errors in segmentation can result in inaccurate calculations of structural parameters. Several approaches to image segmentation have been proposed with varying degrees of automation, ranging from completely manual segmentation, to the selection of input parameters required for computational algorithms. Many of these segmentation algorithms provide speed and reproducibility at the cost of flexibility that manual segmentation provides. In particular, the segmentation of modern and fossil bone in the presence of materials such as desiccated soft tissue, soil matrix or precipitated crystalline material can be difficult. Here we present a free open-source segmentation algorithm application capable of segmenting modern and fossil bone, which also reduces subjective user decisions to a minimum. We compare the effectiveness of this algorithm with another leading method by using both to measure the parameters of a known dimension reference object, as well as to segment an example problematic fossil scan. The results demonstrate that the medical image analysis-clustering method produces accurate segmentations and offers more flexibility than those of equivalent precision. Its free availability, flexibility to deal with non-bone inclusions and limited need for user input give it broad applicability in anthropological, anatomical, and paleontological contexts.

MIA-Clustering: a novel method for segmentation of paleontological material.

Science.gov (United States)

Dunmore, Christopher J; Wollny, Gert; Skinner, Matthew M

2018-01-01

Paleontological research increasingly uses high-resolution micro-computed tomography (μCT) to study the inner architecture of modern and fossil bone material to answer important questions regarding vertebrate evolution. This non-destructive method allows for the measurement of otherwise inaccessible morphology. Digital measurement is predicated on the accurate segmentation of modern or fossilized bone from other structures imaged in μCT scans, as errors in segmentation can result in inaccurate calculations of structural parameters. Several approaches to image segmentation have been proposed with varying degrees of automation, ranging from completely manual segmentation, to the selection of input parameters required for computational algorithms. Many of these segmentation algorithms provide speed and reproducibility at the cost of flexibility that manual segmentation provides. In particular, the segmentation of modern and fossil bone in the presence of materials such as desiccated soft tissue, soil matrix or precipitated crystalline material can be difficult. Here we present a free open-source segmentation algorithm application capable of segmenting modern and fossil bone, which also reduces subjective user decisions to a minimum. We compare the effectiveness of this algorithm with another leading method by using both to measure the parameters of a known dimension reference object, as well as to segment an example problematic fossil scan. The results demonstrate that the medical image analysis-clustering method produces accurate segmentations and offers more flexibility than those of equivalent precision. Its free availability, flexibility to deal with non-bone inclusions and limited need for user input give it broad applicability in anthropological, anatomical, and paleontological contexts.

A systematic review of image segmentation methodology, used in the additive manufacture of patient-specific 3D printed models of the cardiovascular system

Directory of Open Access Journals (Sweden)

N Byrne

2016-04-01

Full Text Available Background Shortcomings in existing methods of image segmentation preclude the widespread adoption of patient-specific 3D printing as a routine decision-making tool in the care of those with congenital heart disease. We sought to determine the range of cardiovascular segmentation methods and how long each of these methods takes. Methods A systematic review of literature was undertaken. Medical imaging modality, segmentation methods, segmentation time, segmentation descriptive quality (SDQ and segmentation software were recorded. Results Totally 136 studies met the inclusion criteria (1 clinical trial; 80 journal articles; 55 conference, technical and case reports. The most frequently used image segmentation methods were brightness thresholding, region growing and manual editing, as supported by the most popular piece of proprietary software: Mimics (Materialise NV, Leuven, Belgium, 1992–2015. The use of bespoke software developed by individual authors was not uncommon. SDQ indicated that reporting of image segmentation methods was generally poor with only one in three accounts providing sufficient detail for their procedure to be reproduced. Conclusions and implication of key findings Predominantly anecdotal and case reporting precluded rigorous assessment of risk of bias and strength of evidence. This review finds a reliance on manual and semi-automated segmentation methods which demand a high level of expertise and a significant time commitment on the part of the operator. In light of the findings, we have made recommendations regarding reporting of 3D printing studies. We anticipate that these findings will encourage the development of advanced image segmentation methods.

A framework for automatic segmentation in three dimensions of microstructural tomography data

DEFF Research Database (Denmark)

Jørgensen, Peter Stanley; Hansen, Karin Vels; Larsen, Rasmus

2010-01-01

Routine use of quantitative three dimensional analysis of material microstructure by in particular, focused ion beam (FIB) serial sectioning is generally restricted by the time consuming task of manually delineating structures within each image slice or the quality of manual and automatic...... segmentation schemes. We present here a framework for performing automatic segmentation of complex microstructures using a level set method. The technique is based on numerical approximations to partial differential equations to evolve a 3D surface to capture the phase boundaries. Vector fields derived from...

Operative outcomes of conventional specimen radiography versus in-operating room specimen radiography in radioactive seed-localized segmental mastectomies.

Science.gov (United States)

Rhee, Daniel; Pockaj, Barbara; Wasif, Nabil; Stucky, Chee-Chee; Pizzitola, Victor; Giurescu, Marina; Patel, Bhavika; McCarthy, Janice; Gray, Richard

2018-01-01

In-operating room specimen radiography (ORSR) has not been studied among women undergoing radioactive seed localization (RSL) for breast cancer surgery and had the potential to decrease operative time and perhaps improve intraoperative margin management. One hundred consecutive RSL segmental mastectomies among 98 patients using ORSR were compared to 100 consecutive segmental mastectomies among 98 patients utilizing conventional radiography (CSR) prior to the initiation of ORSR from December 2013 to January 2015 after radioactive seed localization. Final pathologic margins were considered to be 10 mm for all cases of no residual disease after biopsy or neoadjuvant therapy, but such patients were excluded from analyses involving tumor size. All patients' specimens were subjected to intraoperative pathologic consultation in addition to ORSR or CSR. The median age of the cohort was 65 years (range 36-97), and the median tumor size was 1 cm. There were no differences between the ORSR and CSR groups in age, tumor size, percentage of cases with only DCIS, and percentage of cases with microcalcifications. The ORSR group had a statistically significant lower BMI. Mean operative time from cut-to-close was not significantly different (ORSR 77 min, SD 24.8 vs CSR 76 min, SD 24.8, p = 0.75). There was no statistical difference in mean closest final pathologic margin (4.99 mm, SD 3.3 vs 4.88 mm, SD 3.5, p = 0.9). The percentage undergoing intraoperative margin re-excision (ORSR 40%, CR 47%, p = 0.31) and the mean total number of margins excised intraoperatively (ORSR 0.9, CR 1.0 p = 0.65) were similar. The rate of any margin CSR; this difference was not statistically significant (p = 0.25). The mean ratio of segmental mastectomy volume to maximum tumor diameter was less for ORSR (82.7cm2 vs 139.4cm2, p = 0.014). ORSR for RSL breast surgery, in the setting of routine intraoperative pathology consultation, does not significantly impact operative time, the rate or

IFRS 8 OPERATING SEGMENTS: Eine Untersuchung der erstmaligen Anwendung in der Schweiz

OpenAIRE

Meyer, C; Weiss, S

2010-01-01

Seit dem 1. Januar 2009 sind kotierte IFRS-Anwender verpflichtet, eine Segmentberichterstattung nach IFRS 8 zu erstellen. Anhand einer Analyse der Geschäftsberichte 2009 der an der SIX Swiss Exchange kotierten Unternehmen soll ein Überblick über die erstmalige Anwendung von IFRS 8 "Operating Segments" in der Schweiz gewonnen werden.

Semi-automatic segmentation of myocardium at risk in T2-weighted cardiovascular magnetic resonance.

Science.gov (United States)

Sjögren, Jane; Ubachs, Joey F A; Engblom, Henrik; Carlsson, Marcus; Arheden, Håkan; Heiberg, Einar

2012-01-31

T2-weighted cardiovascular magnetic resonance (CMR) has been shown to be a promising technique for determination of ischemic myocardium, referred to as myocardium at risk (MaR), after an acute coronary event. Quantification of MaR in T2-weighted CMR has been proposed to be performed by manual delineation or the threshold methods of two standard deviations from remote (2SD), full width half maximum intensity (FWHM) or Otsu. However, manual delineation is subjective and threshold methods have inherent limitations related to threshold definition and lack of a priori information about cardiac anatomy and physiology. Therefore, the aim of this study was to develop an automatic segmentation algorithm for quantification of MaR using anatomical a priori information. Forty-seven patients with first-time acute ST-elevation myocardial infarction underwent T2-weighted CMR within 1 week after admission. Endocardial and epicardial borders of the left ventricle, as well as the hyper enhanced MaR regions were manually delineated by experienced observers and used as reference method. A new automatic segmentation algorithm, called Segment MaR, defines the MaR region as the continuous region most probable of being MaR, by estimating the intensities of normal myocardium and MaR with an expectation maximization algorithm and restricting the MaR region by an a priori model of the maximal extent for the user defined culprit artery. The segmentation by Segment MaR was compared against inter observer variability of manual delineation and the threshold methods of 2SD, FWHM and Otsu. MaR was 32.9 ± 10.9% of left ventricular mass (LVM) when assessed by the reference observer and 31.0 ± 8.8% of LVM assessed by Segment MaR. The bias and correlation was, -1.9 ± 6.4% of LVM, R = 0.81 (p Segment MaR, -2.3 ± 4.9%, R = 0.91 (p Segment MaR and manually assessed MaR in T2-weighted CMR. Thus, the proposed algorithm seems to be a promising, objective method for standardized MaR quantification in T2

Operations Manual for Incident and Emergency Communication. Date Effective: 1 June 2012

International Nuclear Information System (INIS)

2012-01-01

The Convention on Early Notification of a Nuclear Accident (the 'Early Notification Convention') and the Convention on Assistance in the Case of a Nuclear Accident or Radiological Emergency (the 'Assistance Convention') are the prime legal instruments that establish an international framework to facilitate the exchange of information and the prompt provision of assistance in the event of a nuclear or radiological incident or emergency, with the aim of minimizing the consequences. The International Atomic Energy Agency (IAEA) has specific functions assigned to it under these Conventions. The arrangements provided between the IAEA, the IAEA's Member States and/or Parties to one or both Conventions, all other relevant international intergovernmental organizations (herein referred to as international organizations), and other States for facilitating the implementation of these Conventions - specifically concerning those articles that are operational in nature - are documented in the present Operations Manual for Incident and Emergency Communication (IEComm). IEComm is the successor to the previous Emergency Notification and Assistance Technical Operations Manual (ENATOM), first issued on 18 January 1989. Member States, Parties to the Early Notification and Assistance Conventions, relevant international organizations and other States, have since then regularly received updates to the manual. This manual covers the communication protocols for Contact Points identified under the Early Notification and Assistance Conventions, as well as the protocol for users of the International Nuclear and Radiological Event Scale (INES). Since the last edition of ENATOM, several factors have warranted some modifications to the existing arrangements: changes due to lessons identified from experience in exchanging information during incidents and emergencies, responding to requests for information and assistance during nuclear and radiological incidents and emergencies in the past few

Comparison of human and automatic segmentations of kidneys from CT images

International Nuclear Information System (INIS)

Rao, Manjori; Stough, Joshua; Chi, Y.-Y.; Muller, Keith; Tracton, Gregg; Pizer, Stephen M.; Chaney, Edward L.

2005-01-01

Purpose: A controlled observer study was conducted to compare a method for automatic image segmentation with conventional user-guided segmentation of right and left kidneys from planning computerized tomographic (CT) images. Methods and materials: Deformable shape models called m-reps were used to automatically segment right and left kidneys from 12 target CT images, and the results were compared with careful manual segmentations performed by two human experts. M-rep models were trained based on manual segmentations from a collection of images that did not include the targets. Segmentation using m-reps began with interactive initialization to position the kidney model over the target kidney in the image data. Fully automatic segmentation proceeded through two stages at successively smaller spatial scales. At the first stage, a global similarity transformation of the kidney model was computed to position the model closer to the target kidney. The similarity transformation was followed by large-scale deformations based on principal geodesic analysis (PGA). During the second stage, the medial atoms comprising the m-rep model were deformed one by one. This procedure was iterated until no changes were observed. The transformations and deformations at both stages were driven by optimizing an objective function with two terms. One term penalized the currently deformed m-rep by an amount proportional to its deviation from the mean m-rep derived from PGA of the training segmentations. The second term computed a model-to-image match term based on the goodness of match of the trained intensity template for the currently deformed m-rep with the corresponding intensity data in the target image. Human and m-rep segmentations were compared using quantitative metrics provided in a toolset called Valmet. Metrics reported in this article include (1) percent volume overlap; (2) mean surface distance between two segmentations; and (3) maximum surface separation (Hausdorff distance

Field Operations and Enforcement Manual for Air Pollution Control. Volume II: Control Technology and General Source Inspection.

Science.gov (United States)

Weisburd, Melvin I.

The Field Operations and Enforcement Manual for Air Pollution Control, Volume II, explains in detail the following: technology of source control, modification of operations, particulate control equipment, sulfur dioxide removal systems for power plants, and control equipment for gases and vapors; inspection procedures for general sources, fuel…

A Split-and-Merge-Based Uterine Fibroid Ultrasound Image Segmentation Method in HIFU Therapy.

Directory of Open Access Journals (Sweden)

Menglong Xu

Full Text Available High-intensity focused ultrasound (HIFU therapy has been used to treat uterine fibroids widely and successfully. Uterine fibroid segmentation plays an important role in positioning the target region for HIFU therapy. Presently, it is completed by physicians manually, reducing the efficiency of therapy. Thus, computer-aided segmentation of uterine fibroids benefits the improvement of therapy efficiency. Recently, most computer-aided ultrasound segmentation methods have been based on the framework of contour evolution, such as snakes and level sets. These methods can achieve good performance, although they need an initial contour that influences segmentation results. It is difficult to obtain the initial contour automatically; thus, the initial contour is always obtained manually in many segmentation methods. A split-and-merge-based uterine fibroid segmentation method, which needs no initial contour to ensure less manual intervention, is proposed in this paper. The method first splits the image into many small homogeneous regions called superpixels. A new feature representation method based on texture histogram is employed to characterize each superpixel. Next, the superpixels are merged according to their similarities, which are measured by integrating their Quadratic-Chi texture histogram distances with their space adjacency. Multi-way Ncut is used as the merging criterion, and an adaptive scheme is incorporated to decrease manual intervention further. The method is implemented using Matlab on a personal computer (PC platform with Intel Pentium Dual-Core CPU E5700. The method is validated on forty-two ultrasound images acquired from HIFU therapy. The average running time is 9.54 s. Statistical results showed that SI reaches a value as high as 87.58%, and normHD is 5.18% on average. It has been demonstrated that the proposed method is appropriate for segmentation of uterine fibroids in HIFU pre-treatment imaging and planning.

User Interaction in Semi-Automatic Segmentation of Organs at Risk: a Case Study in Radiotherapy

NARCIS (Netherlands)

A. Ramkumar (Anjana); J. Dolz (Jose); H.A. Kirisli (Hortense); S. Adebahr (Sonja); T. Schimek-Jasch (Tanja); U. Nestle (Ursula); L. Massoptier (Laurent); E. Varga (Edit); P.J. Stappers (P.); W.J. Niessen (Wiro); Y. Song (Yu)

2016-01-01

textabstractAccurate segmentation of organs at risk is an important step in radiotherapy planning. Manual segmentation being a tedious procedure and prone to inter- and intra-observer variability, there is a growing interest in automated segmentation methods. However, automatic methods frequently

46 CFR 160.151-59 - Operating instructions and information for the ship's training manual.

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2010-10-01

... 46 Shipping 6 2010-10-01 2010-10-01 false Operating instructions and information for the ship's training manual. 160.151-59 Section 160.151-59 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) EQUIPMENT, CONSTRUCTION, AND MATERIALS: SPECIFICATIONS AND APPROVAL LIFESAVING EQUIPMENT Inflatable Liferafts (SOLAS) § 160.151-59...

A semi-automated volumetric software for segmentation and perfusion parameter quantification of brain tumors using 320-row multidetector computed tomography: a validation study

Energy Technology Data Exchange (ETDEWEB)

Chae, Soo Young; Suh, Sangil; Ryoo, Inseon; Park, Arim; Seol, Hae Young [Korea University Guro Hospital, Department of Radiology, Seoul (Korea, Republic of); Noh, Kyoung Jin [Soonchunhyang University, Department of Electronic Engineering, Asan (Korea, Republic of); Shim, Hackjoon [Toshiba Medical Systems Korea Co., Seoul (Korea, Republic of)

2017-05-15

We developed a semi-automated volumetric software, NPerfusion, to segment brain tumors and quantify perfusion parameters on whole-brain CT perfusion (WBCTP) images. The purpose of this study was to assess the feasibility of the software and to validate its performance compared with manual segmentation. Twenty-nine patients with pathologically proven brain tumors who underwent preoperative WBCTP between August 2012 and February 2015 were included. Three perfusion parameters, arterial flow (AF), equivalent blood volume (EBV), and Patlak flow (PF, which is a measure of permeability of capillaries), of brain tumors were generated by a commercial software and then quantified volumetrically by NPerfusion, which also semi-automatically segmented tumor boundaries. The quantification was validated by comparison with that of manual segmentation in terms of the concordance correlation coefficient and Bland-Altman analysis. With NPerfusion, we successfully performed segmentation and quantified whole volumetric perfusion parameters of all 29 brain tumors that showed consistent perfusion trends with previous studies. The validation of the perfusion parameter quantification exhibited almost perfect agreement with manual segmentation, with Lin concordance correlation coefficients (ρ {sub c}) for AF, EBV, and PF of 0.9988, 0.9994, and 0.9976, respectively. On Bland-Altman analysis, most differences between this software and manual segmentation on the commercial software were within the limit of agreement. NPerfusion successfully performs segmentation of brain tumors and calculates perfusion parameters of brain tumors. We validated this semi-automated segmentation software by comparing it with manual segmentation. NPerfusion can be used to calculate volumetric perfusion parameters of brain tumors from WBCTP. (orig.)

A semi-automated volumetric software for segmentation and perfusion parameter quantification of brain tumors using 320-row multidetector computed tomography: a validation study.

Science.gov (United States)

Chae, Soo Young; Suh, Sangil; Ryoo, Inseon; Park, Arim; Noh, Kyoung Jin; Shim, Hackjoon; Seol, Hae Young

2017-05-01

We developed a semi-automated volumetric software, NPerfusion, to segment brain tumors and quantify perfusion parameters on whole-brain CT perfusion (WBCTP) images. The purpose of this study was to assess the feasibility of the software and to validate its performance compared with manual segmentation. Twenty-nine patients with pathologically proven brain tumors who underwent preoperative WBCTP between August 2012 and February 2015 were included. Three perfusion parameters, arterial flow (AF), equivalent blood volume (EBV), and Patlak flow (PF, which is a measure of permeability of capillaries), of brain tumors were generated by a commercial software and then quantified volumetrically by NPerfusion, which also semi-automatically segmented tumor boundaries. The quantification was validated by comparison with that of manual segmentation in terms of the concordance correlation coefficient and Bland-Altman analysis. With NPerfusion, we successfully performed segmentation and quantified whole volumetric perfusion parameters of all 29 brain tumors that showed consistent perfusion trends with previous studies. The validation of the perfusion parameter quantification exhibited almost perfect agreement with manual segmentation, with Lin concordance correlation coefficients (ρ c ) for AF, EBV, and PF of 0.9988, 0.9994, and 0.9976, respectively. On Bland-Altman analysis, most differences between this software and manual segmentation on the commercial software were within the limit of agreement. NPerfusion successfully performs segmentation of brain tumors and calculates perfusion parameters of brain tumors. We validated this semi-automated segmentation software by comparing it with manual segmentation. NPerfusion can be used to calculate volumetric perfusion parameters of brain tumors from WBCTP.

Operation and maintenance manual for septic holding tank system for project W-519, two double-wide construction support trailers

International Nuclear Information System (INIS)

MORTIMER, C.S.

1999-01-01

This manual was prepared to provide detailed information for the operation and maintenance of the sanitary wastewater holding system. It sets forth system operation and maintenance as well as failure response procedures

Gamifying Video Object Segmentation.

Science.gov (United States)

Spampinato, Concetto; Palazzo, Simone; Giordano, Daniela

2017-10-01

Video object segmentation can be considered as one of the most challenging computer vision problems. Indeed, so far, no existing solution is able to effectively deal with the peculiarities of real-world videos, especially in cases of articulated motion and object occlusions; limitations that appear more evident when we compare the performance of automated methods with the human one. However, manually segmenting objects in videos is largely impractical as it requires a lot of time and concentration. To address this problem, in this paper we propose an interactive video object segmentation method, which exploits, on one hand, the capability of humans to identify correctly objects in visual scenes, and on the other hand, the collective human brainpower to solve challenging and large-scale tasks. In particular, our method relies on a game with a purpose to collect human inputs on object locations, followed by an accurate segmentation phase achieved by optimizing an energy function encoding spatial and temporal constraints between object regions as well as human-provided location priors. Performance analysis carried out on complex video benchmarks, and exploiting data provided by over 60 users, demonstrated that our method shows a better trade-off between annotation times and segmentation accuracy than interactive video annotation and automated video object segmentation approaches.

Computer input devices: neutral party or source of significant error in manual lesion segmentation?

Science.gov (United States)

Chen, James Y; Seagull, F Jacob; Nagy, Paul; Lakhani, Paras; Melhem, Elias R; Siegel, Eliot L; Safdar, Nabile M

2011-02-01

Lesion segmentation involves outlining the contour of an abnormality on an image to distinguish boundaries between normal and abnormal tissue and is essential to track malignant and benign disease in medical imaging for clinical, research, and treatment purposes. A laser optical mouse and a graphics tablet were used by radiologists to segment 12 simulated reference lesions per subject in two groups (one group comprised three lesion morphologies in two sizes, one for each input device for each device two sets of six, composed of three morphologies in two sizes each). Time for segmentation was recorded. Subjects completed an opinion survey following segmentation. Error in contour segmentation was calculated using root mean square error. Error in area of segmentation was calculated compared to the reference lesion. 11 radiologists segmented a total of 132 simulated lesions. Overall error in contour segmentation was less with the graphics tablet than with the mouse (P Error in area of segmentation was not significantly different between the tablet and the mouse (P = 0.62). Time for segmentation was less with the tablet than the mouse (P = 0.011). All subjects preferred the graphics tablet for future segmentation (P = 0.011) and felt subjectively that the tablet was faster, easier, and more accurate (P = 0.0005). For purposes in which accuracy in contour of lesion segmentation is of the greater importance, the graphics tablet is superior to the mouse in accuracy with a small speed benefit. For purposes in which accuracy of area of lesion segmentation is of greater importance, the graphics tablet and mouse are equally accurate.

Large deep neural networks for MS lesion segmentation

Science.gov (United States)

Prieto, Juan C.; Cavallari, Michele; Palotai, Miklos; Morales Pinzon, Alfredo; Egorova, Svetlana; Styner, Martin; Guttmann, Charles R. G.

2017-02-01

Multiple sclerosis (MS) is a multi-factorial autoimmune disorder, characterized by spatial and temporal dissemination of brain lesions that are visible in T2-weighted and Proton Density (PD) MRI. Assessment of lesion burden and is useful for monitoring the course of the disease, and assessing correlates of clinical outcomes. Although there are established semi-automated methods to measure lesion volume, most of them require human interaction and editing, which are time consuming and limits the ability to analyze large sets of data with high accuracy. The primary objective of this work is to improve existing segmentation algorithms and accelerate the time consuming operation of identifying and validating MS lesions. In this paper, a Deep Neural Network for MS Lesion Segmentation is implemented. The MS lesion samples are extracted from the Partners Comprehensive Longitudinal Investigation of Multiple Sclerosis (CLIMB) study. A set of 900 subjects with T2, PD and a manually corrected label map images were used to train a Deep Neural Network and identify MS lesions. Initial tests using this network achieved a 90% accuracy rate. A secondary goal was to enable this data repository for big data analysis by using this algorithm to segment the remaining cases available in the CLIMB repository.

In-vivo segmentation and quantification of coronary lesions by optical coherence tomography images for a lesion type definition and stenosis grading.

Science.gov (United States)

Celi, Simona; Berti, Sergio

2014-10-01

Optical coherence tomography (OCT) is a catheter-based medical imaging technique that produces cross-sectional images of blood vessels. This technique is particularly useful for studying coronary atherosclerosis. In this paper, we present a new framework that allows a segmentation and quantification of OCT images of coronary arteries to define the plaque type and stenosis grading. These analyses are usually carried out on-line on the OCT-workstation where measuring is mainly operator-dependent and mouse-based. The aim of this program is to simplify and improve the processing of OCT images for morphometric investigations and to present a fast procedure to obtain 3D geometrical models that can also be used for external purposes such as for finite element simulations. The main phases of our toolbox are the lumen segmentation and the identification of the main tissues in the artery wall. We validated the proposed method with identification and segmentation manually performed by expert OCT readers. The method was evaluated on ten datasets from clinical routine and the validation was performed on 210 images randomly extracted from the pullbacks. Our results show that automated segmentation of the vessel and of the tissue components are possible off-line with a precision that is comparable to manual segmentation for the tissue component and to the proprietary-OCT-console for the lumen segmentation. Several OCT sections have been processed to provide clinical outcome. Copyright © 2014 Elsevier B.V. All rights reserved.

User Interaction in Semi-Automatic Segmentation of Organs at Risk : A Case Study in Radiotherapy

NARCIS (Netherlands)

Ramkumar, A.; Dolz, J.; Kirisli, H.A.; Adebahr, S.; Schimek-Jasch, T.; Nestle, U.; Massoptier, L.; Varga, E.; Stappers, P.J.; Niessen, W.J.; Song, Y.

2015-01-01

Accurate segmentation of organs at risk is an important step in radiotherapy planning. Manual segmentation being a tedious procedure and prone to inter- and intra-observer variability, there is a growing interest in automated segmentation methods. However, automatic methods frequently fail to

Dictionary Based Segmentation in Volumes

DEFF Research Database (Denmark)

Emerson, Monica Jane; Jespersen, Kristine Munk; Jørgensen, Peter Stanley

Method for supervised segmentation of volumetric data. The method is trained from manual annotations, and these annotations make the method very flexible, which we demonstrate in our experiments. Our method infers label information locally by matching the pattern in a neighborhood around a voxel ...... to a dictionary, and hereby accounts for the volume texture....

Using deep learning to segment breast and fibroglandular tissue in MRI volumes.

Science.gov (United States)

Dalmış, Mehmet Ufuk; Litjens, Geert; Holland, Katharina; Setio, Arnaud; Mann, Ritse; Karssemeijer, Nico; Gubern-Mérida, Albert

2017-02-01

Automated segmentation of breast and fibroglandular tissue (FGT) is required for various computer-aided applications of breast MRI. Traditional image analysis and computer vision techniques, such atlas, template matching, or, edge and surface detection, have been applied to solve this task. However, applicability of these methods is usually limited by the characteristics of the images used in the study datasets, while breast MRI varies with respect to the different MRI protocols used, in addition to the variability in breast shapes. All this variability, in addition to various MRI artifacts, makes it a challenging task to develop a robust breast and FGT segmentation method using traditional approaches. Therefore, in this study, we investigated the use of a deep-learning approach known as "U-net." We used a dataset of 66 breast MRI's randomly selected from our scientific archive, which includes five different MRI acquisition protocols and breasts from four breast density categories in a balanced distribution. To prepare reference segmentations, we manually segmented breast and FGT for all images using an in-house developed workstation. We experimented with the application of U-net in two different ways for breast and FGT segmentation. In the first method, following the same pipeline used in traditional approaches, we trained two consecutive (2C) U-nets: first for segmenting the breast in the whole MRI volume and the second for segmenting FGT inside the segmented breast. In the second method, we used a single 3-class (3C) U-net, which performs both tasks simultaneously by segmenting the volume into three regions: nonbreast, fat inside the breast, and FGT inside the breast. For comparison, we applied two existing and published methods to our dataset: an atlas-based method and a sheetness-based method. We used Dice Similarity Coefficient (DSC) to measure the performances of the automated methods, with respect to the manual segmentations. Additionally, we computed

Automated segmentation of blood-flow regions in large thoracic arteries using 3D-cine PC-MRI measurements.

Science.gov (United States)

van Pelt, Roy; Nguyen, Huy; ter Haar Romeny, Bart; Vilanova, Anna

2012-03-01

Quantitative analysis of vascular blood flow, acquired by phase-contrast MRI, requires accurate segmentation of the vessel lumen. In clinical practice, 2D-cine velocity-encoded slices are inspected, and the lumen is segmented manually. However, segmentation of time-resolved volumetric blood-flow measurements is a tedious and time-consuming task requiring automation. Automated segmentation of large thoracic arteries, based solely on the 3D-cine phase-contrast MRI (PC-MRI) blood-flow data, was done. An active surface model, which is fast and topologically stable, was used. The active surface model requires an initial surface, approximating the desired segmentation. A method to generate this surface was developed based on a voxel-wise temporal maximum of blood-flow velocities. The active surface model balances forces, based on the surface structure and image features derived from the blood-flow data. The segmentation results were validated using volunteer studies, including time-resolved 3D and 2D blood-flow data. The segmented surface was intersected with a velocity-encoded PC-MRI slice, resulting in a cross-sectional contour of the lumen. These cross-sections were compared to reference contours that were manually delineated on high-resolution 2D-cine slices. The automated approach closely approximates the manual blood-flow segmentations, with error distances on the order of the voxel size. The initial surface provides a close approximation of the desired luminal geometry. This improves the convergence time of the active surface and facilitates parametrization. An active surface approach for vessel lumen segmentation was developed, suitable for quantitative analysis of 3D-cine PC-MRI blood-flow data. As opposed to prior thresholding and level-set approaches, the active surface model is topologically stable. A method to generate an initial approximate surface was developed, and various features that influence the segmentation model were evaluated. The active surface

Twelve automated thresholding methods for segmentation of PET images: a phantom study

International Nuclear Information System (INIS)

Prieto, Elena; Peñuelas, Iván; Martí-Climent, Josep M; Lecumberri, Pablo; Gómez, Marisol; Pagola, Miguel; Bilbao, Izaskun; Ecay, Margarita

2012-01-01

Tumor volume delineation over positron emission tomography (PET) images is of great interest for proper diagnosis and therapy planning. However, standard segmentation techniques (manual or semi-automated) are operator dependent and time consuming while fully automated procedures are cumbersome or require complex mathematical development. The aim of this study was to segment PET images in a fully automated way by implementing a set of 12 automated thresholding algorithms, classical in the fields of optical character recognition, tissue engineering or non-destructive testing images in high-tech structures. Automated thresholding algorithms select a specific threshold for each image without any a priori spatial information of the segmented object or any special calibration of the tomograph, as opposed to usual thresholding methods for PET. Spherical 18 F-filled objects of different volumes were acquired on clinical PET/CT and on a small animal PET scanner, with three different signal-to-background ratios. Images were segmented with 12 automatic thresholding algorithms and results were compared with the standard segmentation reference, a threshold at 42% of the maximum uptake. Ridler and Ramesh thresholding algorithms based on clustering and histogram-shape information, respectively, provided better results that the classical 42%-based threshold (p < 0.05). We have herein demonstrated that fully automated thresholding algorithms can provide better results than classical PET segmentation tools. (paper)

Statistical shape (ASM) and appearance (AAM) models for the segmentation of the cerebellum in fetal ultrasound

Science.gov (United States)

Reyes López, Misael; Arámbula Cosío, Fernando

2017-11-01

The cerebellum is an important structure to determine the gestational age of the fetus, moreover most of the abnormalities it presents are related to growth disorders. In this work, we present the results of the segmentation of the fetal cerebellum applying statistical shape and appearance models. Both models were tested on ultrasound images of the fetal brain taken from 23 pregnant women, between 18 and 24 gestational weeks. The accuracy results obtained on 11 ultrasound images show a mean Hausdorff distance of 6.08 mm between the manual segmentation and the segmentation using active shape model, and a mean Hausdorff distance of 7.54 mm between the manual segmentation and the segmentation using active appearance model. The reported results demonstrate that the active shape model is more robust in the segmentation of the fetal cerebellum in ultrasound images.

Time Series Modeling of Human Operator Dynamics in Manual Control Tasks

Science.gov (United States)

Biezad, D. J.; Schmidt, D. K.

1984-01-01

A time-series technique is presented for identifying the dynamic characteristics of the human operator in manual control tasks from relatively short records of experimental data. Control of system excitation signals used in the identification is not required. The approach is a multi-channel identification technique for modeling multi-input/multi-output situations. The method presented includes statistical tests for validity, is designed for digital computation, and yields estimates for the frequency response of the human operator. A comprehensive relative power analysis may also be performed for validated models. This method is applied to several sets of experimental data; the results are discussed and shown to compare favorably with previous research findings. New results are also presented for a multi-input task that was previously modeled to demonstrate the strengths of the method.

Manually operated pile driver for use in the south Iraqi Marshlands

Directory of Open Access Journals (Sweden)

Massimo Monti

2013-09-01

Full Text Available Anthropizations are necessary to implement the maintenance, recovery and utilization of wetlands. These interventions should be sustainable in every sense, in particular they should be marked by a low environmental impact. In general this aim can be achieved by using natural materials and carrying out procedures minimally invasive. In Developing Countries the latter point is often supported by the lack of equipment and energy availability, normally obtainable in Industrialized Countries. In practice, to build micro-infrastructures with the above said characteristics, it is normally necessary to drive poles, in our case in wood, in marshland’s soil. In order to accomplish this task a manually operated pile driver was designed and built. To operate in the water, a floating pier consisting of removable modular elements was also designed.

Auto-segmentation of low-risk clinical target volume for head and neck radiation therapy.

Science.gov (United States)

Yang, Jinzhong; Beadle, Beth M; Garden, Adam S; Gunn, Brandon; Rosenthal, David; Ang, Kian; Frank, Steven; Williamson, Ryan; Balter, Peter; Court, Laurence; Dong, Lei

2014-01-01

To investigate atlas-based auto-segmentation methods to improve the quality of the delineation of low-risk clinical target volumes (CTVs) of unilateral tonsil cancers. Sixteen patients received intensity modulated radiation therapy for left tonsil tumors. These patients were treated by a total of 8 oncologists, who delineated all contours manually on the planning CT image. We chose 6 of the patients as atlas cases and used atlas-based auto-segmentation to map each the atlas CTV to the other 10 patients (test patients). For each test patient, the final contour was produced by combining the 6 individual segmentations from the atlases using the simultaneous truth and performance level estimation algorithm. In addition, for each test patient, we identified a single atlas that produced deformed contours best matching the physician's manual contours. The auto-segmented contours were compared with the physician's manual contours using the slice-wise Hausdorff distance (HD), the slice-wise Dice similarity coefficient (DSC), and a total volume overlap index. No single atlas consistently produced good results for all 10 test cases. The multiatlas segmentation achieved a good agreement between auto-segmented contours and manual contours, with a median slice-wise HD of 7.4 ± 1.0 mm, median slice-wise DSC of 80.2% ± 5.9%, and total volume overlap of 77.8% ± 3.3% over the 10 test cases. For radiation oncologists who contoured both the test case and one of the atlas cases, the best atlas for a test case had almost always been contoured by the oncologist who had contoured that test case, indicating that individual physician's practice dominated in target delineation and was an important factor in optimal atlas selection. Multiatlas segmentation may improve the quality of CTV delineation in clinical practice for unilateral tonsil cancers. We also showed that individual physician's practice was an important factor in selecting the optimal atlas for atlas-based auto-segmentation

Radiological Control Manual

Energy Technology Data Exchange (ETDEWEB)

1993-04-01

This manual has been prepared by Lawrence Berkeley Laboratory to provide guidance for site-specific additions, supplements, and clarifications to the DOE Radiological Control Manual. The guidance provided in this manual is based on the requirements given in Title 10 Code of Federal Regulations Part 835, Radiation Protection for Occupational Workers, DOE Order 5480.11, Radiation Protection for Occupational Workers, and the DOE Radiological Control Manual. The topics covered are (1) excellence in radiological control, (2) radiological standards, (3) conduct of radiological work, (4) radioactive materials, (5) radiological health support operations, (6) training and qualification, and (7) radiological records.

Radiological Control Manual

International Nuclear Information System (INIS)

1993-04-01

This manual has been prepared by Lawrence Berkeley Laboratory to provide guidance for site-specific additions, supplements, and clarifications to the DOE Radiological Control Manual. The guidance provided in this manual is based on the requirements given in Title 10 Code of Federal Regulations Part 835, Radiation Protection for Occupational Workers, DOE Order 5480.11, Radiation Protection for Occupational Workers, and the DOE Radiological Control Manual. The topics covered are (1) excellence in radiological control, (2) radiological standards, (3) conduct of radiological work, (4) radioactive materials, (5) radiological health support operations, (6) training and qualification, and (7) radiological records

Fully automatic GBM segmentation in the TCGA-GBM dataset: Prognosis and correlation with VASARI features.

Science.gov (United States)

Rios Velazquez, Emmanuel; Meier, Raphael; Dunn, William D; Alexander, Brian; Wiest, Roland; Bauer, Stefan; Gutman, David A; Reyes, Mauricio; Aerts, Hugo J W L

2015-11-18

Reproducible definition and quantification of imaging biomarkers is essential. We evaluated a fully automatic MR-based segmentation method by comparing it to manually defined sub-volumes by experienced radiologists in the TCGA-GBM dataset, in terms of sub-volume prognosis and association with VASARI features. MRI sets of 109 GBM patients were downloaded from the Cancer Imaging archive. GBM sub-compartments were defined manually and automatically using the Brain Tumor Image Analysis (BraTumIA). Spearman's correlation was used to evaluate the agreement with VASARI features. Prognostic significance was assessed using the C-index. Auto-segmented sub-volumes showed moderate to high agreement with manually delineated volumes (range (r): 0.4 - 0.86). Also, the auto and manual volumes showed similar correlation with VASARI features (auto r = 0.35, 0.43 and 0.36; manual r = 0.17, 0.67, 0.41, for contrast-enhancing, necrosis and edema, respectively). The auto-segmented contrast-enhancing volume and post-contrast abnormal volume showed the highest AUC (0.66, CI: 0.55-0.77 and 0.65, CI: 0.54-0.76), comparable to manually defined volumes (0.64, CI: 0.53-0.75 and 0.63, CI: 0.52-0.74, respectively). BraTumIA and manual tumor sub-compartments showed comparable performance in terms of prognosis and correlation with VASARI features. This method can enable more reproducible definition and quantification of imaging based biomarkers and has potential in high-throughput medical imaging research.

Segmentation of Lung Structures in CT

DEFF Research Database (Denmark)

Lo, Pechin Chien Pau

This thesis proposes and evaluates new algorithms for segmenting various lung structures in computed tomography (CT) images, namely the lungs, airway trees and vessel trees. The main objective of these algorithms is to facilitate a better platform for studying Chronic Obstructive Pulmonary Disease......, 200 randomly selected CT scans were manually evaluated by medical experts, and only negligible or minor errors were found in nine scans. The proposed algorithm has been used to study how changes in smoking behavior affect CT based emphysema quantification. The algorithms for segmenting the airway...

Development of representative magnetic resonance imaging-based atlases of the canine brain and evaluation of three methods for atlas-based segmentation.

Science.gov (United States)

Milne, Marjorie E; Steward, Christopher; Firestone, Simon M; Long, Sam N; O'Brien, Terrence J; Moffat, Bradford A

2016-04-01

To develop representative MRI atlases of the canine brain and to evaluate 3 methods of atlas-based segmentation (ABS). 62 dogs without clinical signs of epilepsy and without MRI evidence of structural brain disease. The MRI scans from 44 dogs were used to develop 4 templates on the basis of brain shape (brachycephalic, mesaticephalic, dolichocephalic, and combined mesaticephalic and dolichocephalic). Atlas labels were generated by segmenting the brain, ventricular system, hippocampal formation, and caudate nuclei. The MRI scans from the remaining 18 dogs were used to evaluate 3 methods of ABS (manual brain extraction and application of a brain shape-specific template [A], automatic brain extraction and application of a brain shape-specific template [B], and manual brain extraction and application of a combined template [C]). The performance of each ABS method was compared by calculation of the Dice and Jaccard coefficients, with manual segmentation used as the gold standard. Method A had the highest mean Jaccard coefficient and was the most accurate ABS method assessed. Measures of overlap for ABS methods that used manual brain extraction (A and C) ranged from 0.75 to 0.95 and compared favorably with repeated measures of overlap for manual extraction, which ranged from 0.88 to 0.97. Atlas-based segmentation was an accurate and repeatable method for segmentation of canine brain structures. It could be performed more rapidly than manual segmentation, which should allow the application of computer-assisted volumetry to large data sets and clinical cases and facilitate neuroimaging research and disease diagnosis.

Semi-automatic segmentation of myocardium at risk in T2-weighted cardiovascular magnetic resonance

Directory of Open Access Journals (Sweden)

Sjögren Jane

2012-01-01

Full Text Available Abstract Background T2-weighted cardiovascular magnetic resonance (CMR has been shown to be a promising technique for determination of ischemic myocardium, referred to as myocardium at risk (MaR, after an acute coronary event. Quantification of MaR in T2-weighted CMR has been proposed to be performed by manual delineation or the threshold methods of two standard deviations from remote (2SD, full width half maximum intensity (FWHM or Otsu. However, manual delineation is subjective and threshold methods have inherent limitations related to threshold definition and lack of a priori information about cardiac anatomy and physiology. Therefore, the aim of this study was to develop an automatic segmentation algorithm for quantification of MaR using anatomical a priori information. Methods Forty-seven patients with first-time acute ST-elevation myocardial infarction underwent T2-weighted CMR within 1 week after admission. Endocardial and epicardial borders of the left ventricle, as well as the hyper enhanced MaR regions were manually delineated by experienced observers and used as reference method. A new automatic segmentation algorithm, called Segment MaR, defines the MaR region as the continuous region most probable of being MaR, by estimating the intensities of normal myocardium and MaR with an expectation maximization algorithm and restricting the MaR region by an a priori model of the maximal extent for the user defined culprit artery. The segmentation by Segment MaR was compared against inter observer variability of manual delineation and the threshold methods of 2SD, FWHM and Otsu. Results MaR was 32.9 ± 10.9% of left ventricular mass (LVM when assessed by the reference observer and 31.0 ± 8.8% of LVM assessed by Segment MaR. The bias and correlation was, -1.9 ± 6.4% of LVM, R = 0.81 (p Conclusions There is a good agreement between automatic Segment MaR and manually assessed MaR in T2-weighted CMR. Thus, the proposed algorithm seems to be a

Brain Tumor Image Segmentation in MRI Image

Science.gov (United States)

Peni Agustin Tjahyaningtijas, Hapsari

2018-04-01

Brain tumor segmentation plays an important role in medical image processing. Treatment of patients with brain tumors is highly dependent on early detection of these tumors. Early detection of brain tumors will improve the patient’s life chances. Diagnosis of brain tumors by experts usually use a manual segmentation that is difficult and time consuming because of the necessary automatic segmentation. Nowadays automatic segmentation is very populer and can be a solution to the problem of tumor brain segmentation with better performance. The purpose of this paper is to provide a review of MRI-based brain tumor segmentation methods. There are number of existing review papers, focusing on traditional methods for MRI-based brain tumor image segmentation. this paper, we focus on the recent trend of automatic segmentation in this field. First, an introduction to brain tumors and methods for brain tumor segmentation is given. Then, the state-of-the-art algorithms with a focus on recent trend of full automatic segmentaion are discussed. Finally, an assessment of the current state is presented and future developments to standardize MRI-based brain tumor segmentation methods into daily clinical routine are addressed.

Automated segmentation of muscle and adipose tissue on CT images for human body composition analysis

Science.gov (United States)

Chung, Howard; Cobzas, Dana; Birdsell, Laura; Lieffers, Jessica; Baracos, Vickie

2009-02-01

The ability to compute body composition in cancer patients lends itself to determining the specific clinical outcomes associated with fat and lean tissue stores. For example, a wasting syndrome of advanced disease associates with shortened survival. Moreover, certain tissue compartments represent sites for drug distribution and are likely determinants of chemotherapy efficacy and toxicity. CT images are abundant, but these cannot be fully exploited unless there exist practical and fast approaches for tissue quantification. Here we propose a fully automated method for segmenting muscle, visceral and subcutaneous adipose tissues, taking the approach of shape modeling for the analysis of skeletal muscle. Muscle shape is represented using PCA encoded Free Form Deformations with respect to a mean shape. The shape model is learned from manually segmented images and used in conjunction with a tissue appearance prior. VAT and SAT are segmented based on the final deformed muscle shape. In comparing the automatic and manual methods, coefficients of variation (COV) (1 - 2%), were similar to or smaller than inter- and intra-observer COVs reported for manual segmentation.

Using trainable segmentation and watershed transform for identifying unilocular and multilocular cysts from ultrasound images of ovarian tumour

Science.gov (United States)

Ibrahim, Dheyaa Ahmed; Al-Assam, Hisham; Du, Hongbo; Jassim, Sabah

2017-05-01

Ovarian masses are categorised into different types of malignant and benign. In order to optimize patient treatment, it is necessary to carry out pre-operational characterisation of the suspect ovarian mass to determine its category. Ultrasound imaging has been widely used in differentiating malignant from benign cases due to its safe and non-intrusive nature, and can be used for determining the number of cysts in the ovary. Presently, the gynaecologist is tasked with manually counting the number of cysts shown on the ultrasound image. This paper proposes, a new approach that automatically segments the ovarian masses and cysts from a static B-mode image. Initially, the method uses a trainable segmentation procedure and a trained neural network classifier to accurately identify the position of the masses and cysts. After that, the borders of the masses can be appraised using watershed transform. The effectiveness of the proposed method has been tested by comparing the number of cysts identified by the method against the manual examination by a gynaecologist. A total of 65 ultrasound images were used for the comparison, and the results showed that the proposed solution is a viable alternative to the manual counting method for accurately determining the number of cysts in a US ovarian image.

Fully automatic detection and segmentation of abdominal aortic thrombus in post-operative CTA images using Deep Convolutional Neural Networks.

Science.gov (United States)

López-Linares, Karen; Aranjuelo, Nerea; Kabongo, Luis; Maclair, Gregory; Lete, Nerea; Ceresa, Mario; García-Familiar, Ainhoa; Macía, Iván; González Ballester, Miguel A

2018-05-01

Computerized Tomography Angiography (CTA) based follow-up of Abdominal Aortic Aneurysms (AAA) treated with Endovascular Aneurysm Repair (EVAR) is essential to evaluate the progress of the patient and detect complications. In this context, accurate quantification of post-operative thrombus volume is required. However, a proper evaluation is hindered by the lack of automatic, robust and reproducible thrombus segmentation algorithms. We propose a new fully automatic approach based on Deep Convolutional Neural Networks (DCNN) for robust and reproducible thrombus region of interest detection and subsequent fine thrombus segmentation. The DetecNet detection network is adapted to perform region of interest extraction from a complete CTA and a new segmentation network architecture, based on Fully Convolutional Networks and a Holistically-Nested Edge Detection Network, is presented. These networks are trained, validated and tested in 13 post-operative CTA volumes of different patients using a 4-fold cross-validation approach to provide more robustness to the results. Our pipeline achieves a Dice score of more than 82% for post-operative thrombus segmentation and provides a mean relative volume difference between ground truth and automatic segmentation that lays within the experienced human observer variance without the need of human intervention in most common cases. Copyright © 2018 Elsevier B.V. All rights reserved.

Algorithms for Cytoplasm Segmentation of Fluorescence Labelled Cells

Directory of Open Access Journals (Sweden)

Carolina Wählby

2002-01-01

Full Text Available Automatic cell segmentation has various applications in cytometry, and while the nucleus is often very distinct and easy to identify, the cytoplasm provides a lot more challenge. A new combination of image analysis algorithms for segmentation of cells imaged by fluorescence microscopy is presented. The algorithm consists of an image pre‐processing step, a general segmentation and merging step followed by a segmentation quality measurement. The quality measurement consists of a statistical analysis of a number of shape descriptive features. Objects that have features that differ to that of correctly segmented single cells can be further processed by a splitting step. By statistical analysis we therefore get a feedback system for separation of clustered cells. After the segmentation is completed, the quality of the final segmentation is evaluated. By training the algorithm on a representative set of training images, the algorithm is made fully automatic for subsequent images created under similar conditions. Automatic cytoplasm segmentation was tested on CHO‐cells stained with calcein. The fully automatic method showed between 89% and 97% correct segmentation as compared to manual segmentation.

Malignant pleural mesothelioma segmentation for photodynamic therapy planning.

Science.gov (United States)

Brahim, Wael; Mestiri, Makram; Betrouni, Nacim; Hamrouni, Kamel

2018-04-01

Medical imaging modalities such as computed tomography (CT) combined with computer-aided diagnostic processing have already become important part of clinical routine specially for pleural diseases. The segmentation of the thoracic cavity represents an extremely important task in medical imaging for different reasons. Multiple features can be extracted by analyzing the thoracic cavity space and these features are signs of pleural diseases including the malignant pleural mesothelioma (MPM) which is the main focus of our research. This paper presents a method that detects the MPM in the thoracic cavity and plans the photodynamic therapy in the preoperative phase. This is achieved by using a texture analysis of the MPM region combined with a thoracic cavity segmentation method. The algorithm to segment the thoracic cavity consists of multiple stages. First, the rib cage structure is segmented using various image processing techniques. We used the segmented rib cage to detect feature points which represent the thoracic cavity boundaries. Next, the proposed method segments the structures of the inner thoracic cage and fits 2D closed curves to the detected pleural cavity features in each slice. The missing bone structures are interpolated using a prior knowledge from manual segmentation performed by an expert. Next, the tumor region is segmented inside the thoracic cavity using a texture analysis approach. Finally, the contact surface between the tumor region and the thoracic cavity curves is reconstructed in order to plan the photodynamic therapy. Using the adjusted output of the thoracic cavity segmentation method and the MPM segmentation method, we evaluated the contact surface generated from these two steps by comparing it to the ground truth. For this evaluation, we used 10 CT scans with pathologically confirmed MPM at stages 1 and 2. We obtained a high similarity rate between the manually planned surface and our proposed method. The average value of Jaccard index

Automated segmentation of reference tissue for prostate cancer localization in dynamic contrast enhanced MRI

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Vos, Pieter C.; Hambrock, Thomas; Barentsz, Jelle O.; Huisman, Henkjan J.

2010-03-01

For pharmacokinetic (PK) analysis of Dynamic Contrast Enhanced (DCE) MRI the arterial input function needs to be estimated. Previously, we demonstrated that PK parameters have a significant better discriminative performance when per patient reference tissue was used, but required manual annotation of reference tissue. In this study we propose a fully automated reference tissue segmentation method that tackles this limitation. The method was tested with our Computer Aided Diagnosis (CADx) system to study the effect on the discriminating performance for differentiating prostate cancer from benign areas in the peripheral zone (PZ). The proposed method automatically segments normal PZ tissue from DCE derived data. First, the bladder is segmented in the start-to-enhance map using the Otsu histogram threshold selection method. Second, the prostate is detected by applying a multi-scale Hessian filter to the relative enhancement map. Third, normal PZ tissue was segmented by threshold and morphological operators. The resulting segmentation was used as reference tissue to estimate the PK parameters. In 39 consecutive patients carcinoma, benign and normal tissue were annotated on MR images by a radiologist and a researcher using whole mount step-section histopathology as reference. PK parameters were computed for each ROI. Features were extracted from the set of ROIs using percentiles to train a support vector machine that was used as classifier. Prospective performance was estimated by means of leave-one-patient-out cross validation. A bootstrap resampling approach with 10,000 iterations was used for estimating the bootstrap mean AUCs and 95% confidence intervals. In total 42 malignant, 29 benign and 37 normal regions were annotated. For all patients, normal PZ was successfully segmented. The diagnostic accuracy obtained for differentiating malignant from benign lesions using a conventional general patient plasma profile showed an accuracy of 0.64 (0.53-0.74). Using the

Evaluation of segmentation algorithms for optical coherence tomography images of ovarian tissue

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Sawyer, Travis W.; Rice, Photini F. S.; Sawyer, David M.; Koevary, Jennifer W.; Barton, Jennifer K.

2018-02-01

Ovarian cancer has the lowest survival rate among all gynecologic cancers due to predominantly late diagnosis. Early detection of ovarian cancer can increase 5-year survival rates from 40% up to 92%, yet no reliable early detection techniques exist. Optical coherence tomography (OCT) is an emerging technique that provides depthresolved, high-resolution images of biological tissue in real time and demonstrates great potential for imaging of ovarian tissue. Mouse models are crucial to quantitatively assess the diagnostic potential of OCT for ovarian cancer imaging; however, due to small organ size, the ovaries must rst be separated from the image background using the process of segmentation. Manual segmentation is time-intensive, as OCT yields three-dimensional data. Furthermore, speckle noise complicates OCT images, frustrating many processing techniques. While much work has investigated noise-reduction and automated segmentation for retinal OCT imaging, little has considered the application to the ovaries, which exhibit higher variance and inhomogeneity than the retina. To address these challenges, we evaluated a set of algorithms to segment OCT images of mouse ovaries. We examined ve preprocessing techniques and six segmentation algorithms. While all pre-processing methods improve segmentation, Gaussian filtering is most effective, showing an improvement of 32% +/- 1.2%. Of the segmentation algorithms, active contours performs best, segmenting with an accuracy of 0.948 +/- 0.012 compared with manual segmentation (1.0 being identical). Nonetheless, further optimization could lead to maximizing the performance for segmenting OCT images of the ovaries.

Automated segmentation of the atrial region and fossa ovalis towards computer-aided planning of inter-atrial wall interventions.

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Morais, Pedro; Vilaça, João L; Queirós, Sandro; Marchi, Alberto; Bourier, Felix; Deisenhofer, Isabel; D'hooge, Jan; Tavares, João Manuel R S

2018-07-01

Image-fusion strategies have been applied to improve inter-atrial septal (IAS) wall minimally-invasive interventions. Hereto, several landmarks are initially identified on richly-detailed datasets throughout the planning stage and then combined with intra-operative images, enhancing the relevant structures and easing the procedure. Nevertheless, such planning is still performed manually, which is time-consuming and not necessarily reproducible, hampering its regular application. In this article, we present a novel automatic strategy to segment the atrial region (left/right atrium and aortic tract) and the fossa ovalis (FO). The method starts by initializing multiple 3D contours based on an atlas-based approach with global transforms only and refining them to the desired anatomy using a competitive segmentation strategy. The obtained contours are then applied to estimate the FO by evaluating both IAS wall thickness and the expected FO spatial location. The proposed method was evaluated in 41 computed tomography datasets, by comparing the atrial region segmentation and FO estimation results against manually delineated contours. The automatic segmentation method presented a performance similar to the state-of-the-art techniques and a high feasibility, failing only in the segmentation of one aortic tract and of one right atrium. The FO estimation method presented an acceptable result in all the patients with a performance comparable to the inter-observer variability. Moreover, it was faster and fully user-interaction free. Hence, the proposed method proved to be feasible to automatically segment the anatomical models for the planning of IAS wall interventions, making it exceptionally attractive for use in the clinical practice. Copyright © 2018 Elsevier B.V. All rights reserved.

Automatic segmentation of the heart in radiotherapy for breast cancer

DEFF Research Database (Denmark)

Laugaard Lorenzen, Ebbe; Ewertz, Marianne; Brink, Carsten

2014-01-01

Background. The aim of this study was to evaluate two fully automatic segmentation methods in comparison with manual delineations for their use in delineating the heart on planning computed tomography (CT) used in radiotherapy for breast cancer. Material and methods. Automatic delineation of heart...... in 15 breast cancer patients was performed by two different automatic delineation systems. Analysis of accuracy and precision of the differences between manual and automatic delineations were evaluated on volume, mean dose, maximum dose and spatial distance differences. Two sets of manual delineations...

Technical report on semiautomatic segmentation using the Adobe Photoshop.

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Park, Jin Seo; Chung, Min Suk; Hwang, Sung Bae; Lee, Yong Sook; Har, Dong-Hwan

2005-12-01

The purpose of this research is to enable users to semiautomatically segment the anatomical structures in magnetic resonance images (MRIs), computerized tomographs (CTs), and other medical images on a personal computer. The segmented images are used for making 3D images, which are helpful to medical education and research. To achieve this purpose, the following trials were performed. The entire body of a volunteer was scanned to make 557 MRIs. On Adobe Photoshop, contours of 19 anatomical structures in the MRIs were semiautomatically drawn using MAGNETIC LASSO TOOL and manually corrected using either LASSO TOOL or DIRECT SELECTION TOOL to make 557 segmented images. In a similar manner, 13 anatomical structures in 8,590 anatomical images were segmented. Proper segmentation was verified by making 3D images from the segmented images. Semiautomatic segmentation using Adobe Photoshop is expected to be widely used for segmentation of anatomical structures in various medical images.

Brain tumor segmentation in MRI by using the fuzzy connectedness method

Science.gov (United States)

Liu, Jian-Guo; Udupa, Jayaram K.; Hackney, David; Moonis, Gul

2001-07-01

The aim of this paper is the precise and accurate quantification of brain tumor via MRI. This is very useful in evaluating disease progression, response to therapy, and the need for changes in treatment plans. We use multiple MRI protocols including FLAIR, T1, and T1 with Gd enhancement to gather information about different aspects of the tumor and its vicinity- edema, active regions, and scar left over due to surgical intervention. We have adapted the fuzzy connectedness framework to segment tumor and to measure its volume. The method requires only limited user interaction in routine clinical MRI. The first step in the process is to apply an intensity normalization method to the images so that the same body region has the same tissue meaning independent of the scanner and patient. Subsequently, a fuzzy connectedness algorithm is utilized to segment the different aspects of the tumor. The system has been tested, for its precision, accuracy, and efficiency, utilizing 40 patient studies. The percent coefficient of variation (% CV) in volume due to operator subjectivity in specifying seeds for fuzzy connectedness segmentation is less than 1%. The mean operator and computer time taken per study is 3 minutes. The package is designed to run under operator supervision. Delineation has been found to agree with the operators' visual inspection most of the time except in some cases when the tumor is close to the boundary of the brain. In the latter case, the scalp is included in the delineation and an operator has to exclude this manually. The methodology is rapid, robust, consistent, yielding highly reproducible measurements, and is likely to become part of the routine evaluation of brain tumor patients in our health system.

Task-based evaluation of segmentation algorithms for diffusion-weighted MRI without using a gold standard

International Nuclear Information System (INIS)

Jha, Abhinav K; Kupinski, Matthew A; Rodríguez, Jeffrey J; Stephen, Renu M; Stopeck, Alison T

2012-01-01

In many studies, the estimation of the apparent diffusion coefficient (ADC) of lesions in visceral organs in diffusion-weighted (DW) magnetic resonance images requires an accurate lesion-segmentation algorithm. To evaluate these lesion-segmentation algorithms, region-overlap measures are used currently. However, the end task from the DW images is accurate ADC estimation, and the region-overlap measures do not evaluate the segmentation algorithms on this task. Moreover, these measures rely on the existence of gold-standard segmentation of the lesion, which is typically unavailable. In this paper, we study the problem of task-based evaluation of segmentation algorithms in DW imaging in the absence of a gold standard. We first show that using manual segmentations instead of gold-standard segmentations for this task-based evaluation is unreliable. We then propose a method to compare the segmentation algorithms that does not require gold-standard or manual segmentation results. The no-gold-standard method estimates the bias and the variance of the error between the true ADC values and the ADC values estimated using the automated segmentation algorithm. The method can be used to rank the segmentation algorithms on the basis of both the ensemble mean square error and precision. We also propose consistency checks for this evaluation technique. (paper)

A supervised framework for lesion segmentation and automated VLSM analyses in left hemispheric stroke

Directory of Open Access Journals (Sweden)

Dorian Pustina

2015-05-01

Full Text Available INTRODUCTION: Voxel-based lesion-symptom mapping (VLSM is conventionally performed using skill and knowledge of experts to manually delineate brain lesions. This process requires time, and is likely to have substantial inter-rater variability. Here, we propose a supervised machine learning framework for lesion segmentation capable of learning from a single modality and existing manual segmentations in order to delineate lesions in new patients. METHODS: Data from 60 patients with chronic stroke aphasia were utilized in the study (age: 59.7±11.5yrs, post-stroke interval: 5±2.9yrs, male/female ratio: 34/26. Using a single T1 image of each subject, additional features were created that provided complementary information, such as, difference from template, tissue segmentation, brain asymmetries, gradient magnitude, and deviances of these images from 80 age and gender matched controls. These features were fed into MRV-NRF (multi-resolution voxel-wise neighborhood random forest; Tustison et al., 2014 prediction algorithm implemented in ANTsR (Avants, 2015. The algorithm incorporates information from each voxel and its surrounding neighbors from all above features, in a hierarchy of random forest predictions from low to high resolution. The validity of the framework was tested with a 6-fold cross validation (i.e., train from 50 subjects, predict 10. The process was repeated ten times, producing ten segmentations for each subject, from which the average solution was binarized. Predicted lesions were compared to manually defined lesions, and VLSM models were built on 4 language measures: repetition and comprehension subscores from the WAB (Kertesz, 1982, WAB-AQ, and PNT naming accuracy (Roach, Schwartz, Martin, Grewal, & Brecher, 1996. RESULTS: Manual and predicted lesion size showed high correlation (r=0.96. Compared to manual lesions, the predicted lesions had a dice overlap of 0.72 (±0.14 STD, a case-wise maximum distance (Hausdorff of 21mm (±16

Volumetric analysis of pelvic hematomas after blunt trauma using semi-automated seeded region growing segmentation: a method validation study.

Science.gov (United States)

Dreizin, David; Bodanapally, Uttam K; Neerchal, Nagaraj; Tirada, Nikki; Patlas, Michael; Herskovits, Edward

2016-11-01

Manually segmented traumatic pelvic hematoma volumes are strongly predictive of active bleeding at conventional angiography, but the method is time intensive, limiting its clinical applicability. We compared volumetric analysis using semi-automated region growing segmentation to manual segmentation and diameter-based size estimates in patients with pelvic hematomas after blunt pelvic trauma. A 14-patient cohort was selected in an anonymous randomized fashion from a dataset of patients with pelvic binders at MDCT, collected retrospectively as part of a HIPAA-compliant IRB-approved study from January 2008 to December 2013. To evaluate intermethod differences, one reader (R1) performed three volume measurements using the manual technique and three volume measurements using the semi-automated technique. To evaluate interobserver differences for semi-automated segmentation, a second reader (R2) performed three semi-automated measurements. One-way analysis of variance was used to compare differences in mean volumes. Time effort was also compared. Correlation between the two methods as well as two shorthand appraisals (greatest diameter, and the ABC/2 method for estimating ellipsoid volumes) was assessed with Spearman's rho (r). Intraobserver variability was lower for semi-automated compared to manual segmentation, with standard deviations ranging between ±5-32 mL and ±17-84 mL, respectively (p = 0.0003). There was no significant difference in mean volumes between the two readers' semi-automated measurements (p = 0.83); however, means were lower for the semi-automated compared with the manual technique (manual: mean and SD 309.6 ± 139 mL; R1 semi-auto: 229.6 ± 88.2 mL, p = 0.004; R2 semi-auto: 243.79 ± 99.7 mL, p = 0.021). Despite differences in means, the correlation between the two methods was very strong and highly significant (r = 0.91, p hematoma volumes correlate strongly with manually segmented volumes. Since semi-automated segmentation

An unsupervised strategy for biomedical image segmentation

Directory of Open Access Journals (Sweden)

Roberto Rodríguez

2010-09-01

Full Text Available Roberto Rodríguez1, Rubén Hernández21Digital Signal Processing Group, Institute of Cybernetics, Mathematics, and Physics, Havana, Cuba; 2Interdisciplinary Professional Unit of Engineering and Advanced Technology, IPN, MexicoAbstract: Many segmentation techniques have been published, and some of them have been widely used in different application problems. Most of these segmentation techniques have been motivated by specific application purposes. Unsupervised methods, which do not assume any prior scene knowledge can be learned to help the segmentation process, and are obviously more challenging than the supervised ones. In this paper, we present an unsupervised strategy for biomedical image segmentation using an algorithm based on recursively applying mean shift filtering, where entropy is used as a stopping criterion. This strategy is proven with many real images, and a comparison is carried out with manual segmentation. With the proposed strategy, errors less than 20% for false positives and 0% for false negatives are obtained.Keywords: segmentation, mean shift, unsupervised segmentation, entropy

Vessel Segmentation in Retinal Images Using Multi-scale Line Operator and K-Means Clustering.

Science.gov (United States)

Saffarzadeh, Vahid Mohammadi; Osareh, Alireza; Shadgar, Bita

2014-04-01

Detecting blood vessels is a vital task in retinal image analysis. The task is more challenging with the presence of bright and dark lesions in retinal images. Here, a method is proposed to detect vessels in both normal and abnormal retinal fundus images based on their linear features. First, the negative impact of bright lesions is reduced by using K-means segmentation in a perceptive space. Then, a multi-scale line operator is utilized to detect vessels while ignoring some of the dark lesions, which have intensity structures different from the line-shaped vessels in the retina. The proposed algorithm is tested on two publicly available STARE and DRIVE databases. The performance of the method is measured by calculating the area under the receiver operating characteristic curve and the segmentation accuracy. The proposed method achieves 0.9483 and 0.9387 localization accuracy against STARE and DRIVE respectively.

Segmentation of the geographic atrophy in spectral-domain optical coherence tomography and fundus autofluorescence images.

Science.gov (United States)

Hu, Zhihong; Medioni, Gerard G; Hernandez, Matthias; Hariri, Amirhossein; Wu, Xiaodong; Sadda, Srinivas R

2013-12-30

Geographic atrophy (GA) is the atrophic late-stage manifestation of age-related macular degeneration (AMD), which may result in severe vision loss and blindness. The purpose of this study was to develop a reliable, effective approach for GA segmentation in both spectral-domain optical coherence tomography (SD-OCT) and fundus autofluorescence (FAF) images using a level set-based approach and to compare the segmentation performance in the two modalities. To identify GA regions in SD-OCT images, three retinal surfaces were first segmented in volumetric SD-OCT images using a double-surface graph search scheme. A two-dimensional (2-D) partial OCT projection image was created from the segmented choroid layer. A level set approach was applied to segment the GA in the partial OCT projection image. In addition, the algorithm was applied to FAF images for the GA segmentation. Twenty randomly chosen macular SD-OCT (Zeiss Cirrus) volumes and 20 corresponding FAF (Heidelberg Spectralis) images were obtained from 20 subjects with GA. The algorithm-defined GA region was compared with consensus manual delineation performed by certified graders. The mean Dice similarity coefficients (DSC) between the algorithm- and manually defined GA regions were 0.87 ± 0.09 in partial OCT projection images and 0.89 ± 0.07 in registered FAF images. The area correlations between them were 0.93 (P segment GA regions in both SD-OCT and FAF images. This approach demonstrated good agreement between the algorithm- and manually defined GA regions within each single modality. The GA segmentation in FAF images performed better than in partial OCT projection images. Across the two modalities, the GA segmentation presented reasonable agreement.

A minimal path searching approach for active shape model (ASM)-based segmentation of the lung

Science.gov (United States)

Guo, Shengwen; Fei, Baowei

2009-02-01

We are developing a minimal path searching method for active shape model (ASM)-based segmentation for detection of lung boundaries on digital radiographs. With the conventional ASM method, the position and shape parameters of the model points are iteratively refined and the target points are updated by the least Mahalanobis distance criterion. We propose an improved searching strategy that extends the searching points in a fan-shape region instead of along the normal direction. A minimal path (MP) deformable model is applied to drive the searching procedure. A statistical shape prior model is incorporated into the segmentation. In order to keep the smoothness of the shape, a smooth constraint is employed to the deformable model. To quantitatively assess the ASM-MP segmentation, we compare the automatic segmentation with manual segmentation for 72 lung digitized radiographs. The distance error between the ASM-MP and manual segmentation is 1.75 +/- 0.33 pixels, while the error is 1.99 +/- 0.45 pixels for the ASM. Our results demonstrate that our ASM-MP method can accurately segment the lung on digital radiographs.

A Minimal Path Searching Approach for Active Shape Model (ASM)-based Segmentation of the Lung.

Science.gov (United States)

Guo, Shengwen; Fei, Baowei

2009-03-27

We are developing a minimal path searching method for active shape model (ASM)-based segmentation for detection of lung boundaries on digital radiographs. With the conventional ASM method, the position and shape parameters of the model points are iteratively refined and the target points are updated by the least Mahalanobis distance criterion. We propose an improved searching strategy that extends the searching points in a fan-shape region instead of along the normal direction. A minimal path (MP) deformable model is applied to drive the searching procedure. A statistical shape prior model is incorporated into the segmentation. In order to keep the smoothness of the shape, a smooth constraint is employed to the deformable model. To quantitatively assess the ASM-MP segmentation, we compare the automatic segmentation with manual segmentation for 72 lung digitized radiographs. The distance error between the ASM-MP and manual segmentation is 1.75 ± 0.33 pixels, while the error is 1.99 ± 0.45 pixels for the ASM. Our results demonstrate that our ASM-MP method can accurately segment the lung on digital radiographs.

Age and Practice Effects on Inter-manual Performance Asymmetry

Directory of Open Access Journals (Sweden)

Karen L Francis

2015-01-01

Full Text Available Manual dexterity declines with increasing age however, the way in which inter-manual asymmetry responds to aging is unclear. Our purpose was to determine the effect of age and practice on inter-manual performance asymmetry in an isometric force pinch line tracing task that varied in difficulty within segments. Thirty right handed participants, 5 males and 5 females in each of three age groups, young (Y20, young-old (O70, and old-old (O80, practiced an isometric force pinch task for 10 trials with each hand on each of five consecutive days. Inter-manual performance asymmetry of the right and left hands was analyzed with a repeated measures ANOVA of asymmetry with age groups, practice, task difficulty, and hand as factors. The within-individual magnitude of asymmetry was also analyzed with a repeated measures ANOVA of manual asymmetry calculated as an asymmetry index (AI. Post hoc pair-wise comparisons were performed when significance was found. We observed no inter-manual performance asymmetry on this isometric tracing task among any of the age groups, either in the hand performance differences or in the magnitude of the asymmetry index (AI. Age and practice interacted in terms of manual performance: the Y20 and O70 group improved accuracy and task time across the five days of practice but the O80 group did not. However, practice did not differentially affect the AI for accuracy or task time for any group. Accuracy of performance of the two hands was differentially affected by practice. All age groups exhibited poorer performance and larger AIs on the most difficult segments of the task (3 and 6 and this did not change with practice.

A new 2D segmentation method based on dynamic programming applied to computer aided detection in mammography

International Nuclear Information System (INIS)

Timp, Sheila; Karssemeijer, Nico

2004-01-01

Mass segmentation plays a crucial role in computer-aided diagnosis (CAD) systems for classification of suspicious regions as normal, benign, or malignant. In this article we present a robust and automated segmentation technique--based on dynamic programming--to segment mass lesions from surrounding tissue. In addition, we propose an efficient algorithm to guarantee resulting contours to be closed. The segmentation method based on dynamic programming was quantitatively compared with two other automated segmentation methods (region growing and the discrete contour model) on a dataset of 1210 masses. For each mass an overlap criterion was calculated to determine the similarity with manual segmentation. The mean overlap percentage for dynamic programming was 0.69, for the other two methods 0.60 and 0.59, respectively. The difference in overlap percentage was statistically significant. To study the influence of the segmentation method on the performance of a CAD system two additional experiments were carried out. The first experiment studied the detection performance of the CAD system for the different segmentation methods. Free-response receiver operating characteristics analysis showed that the detection performance was nearly identical for the three segmentation methods. In the second experiment the ability of the classifier to discriminate between malignant and benign lesions was studied. For region based evaluation the area A z under the receiver operating characteristics curve was 0.74 for dynamic programming, 0.72 for the discrete contour model, and 0.67 for region growing. The difference in A z values obtained by the dynamic programming method and region growing was statistically significant. The differences between other methods were not significant

Scorpion image segmentation system

Science.gov (United States)

Joseph, E.; Aibinu, A. M.; Sadiq, B. A.; Bello Salau, H.; Salami, M. J. E.

2013-12-01

Death as a result of scorpion sting has been a major public health problem in developing countries. Despite the high rate of death as a result of scorpion sting, little report exists in literature of intelligent device and system for automatic detection of scorpion. This paper proposed a digital image processing approach based on the floresencing characteristics of Scorpion under Ultra-violet (UV) light for automatic detection and identification of scorpion. The acquired UV-based images undergo pre-processing to equalize uneven illumination and colour space channel separation. The extracted channels are then segmented into two non-overlapping classes. It has been observed that simple thresholding of the green channel of the acquired RGB UV-based image is sufficient for segmenting Scorpion from other background components in the acquired image. Two approaches to image segmentation have also been proposed in this work, namely, the simple average segmentation technique and K-means image segmentation. The proposed algorithm has been tested on over 40 UV scorpion images obtained from different part of the world and results obtained show an average accuracy of 97.7% in correctly classifying the pixel into two non-overlapping clusters. The proposed 1system will eliminate the problem associated with some of the existing manual approaches presently in use for scorpion detection.

Optoelectronics circuits manual

CERN Document Server

Marston, R M

2013-01-01

Optoelectronics Circuits Manual covers the basic principles and characteristics of the best known types of optoelectronic devices, as well as the practical applications of many of these optoelectronic devices. The book describes LED display circuits and LED dot- and bar-graph circuits and discusses the applications of seven-segment displays, light-sensitive devices, optocouplers, and a variety of brightness control techniques. The text also tackles infrared light-beam alarms and multichannel remote control systems. The book provides practical user information and circuitry and illustrations.

Quantification and visualization of carotid segmentation accuracy and precision using a 2D standardized carotid map

International Nuclear Information System (INIS)

Chiu, Bernard; Ukwatta, Eranga; Shavakh, Shadi; Fenster, Aaron

2013-01-01

This paper describes a framework for vascular image segmentation evaluation. Since the size of vessel wall and plaque burden is defined by the lumen and wall boundaries in vascular segmentation, these two boundaries should be considered as a pair in statistical evaluation of a segmentation algorithm. This work proposed statistical metrics to evaluate the difference of local vessel wall thickness (VWT) produced by manual and algorithm-based semi-automatic segmentation methods (ΔT) with the local segmentation standard deviation of the wall and lumen boundaries considered. ΔT was further approximately decomposed into the local wall and lumen boundary differences (ΔW and ΔL respectively) in order to provide information regarding which of the wall and lumen segmentation errors contribute more to the VWT difference. In this study, the lumen and wall boundaries in 3D carotid ultrasound images acquired for 21 subjects were each segmented five times manually and by a level-set segmentation algorithm. The (absolute) difference measures (i.e., ΔT, ΔW, ΔL and their absolute values) and the pooled local standard deviation of manually and algorithmically segmented wall and lumen boundaries were computed for each subject and represented in a 2D standardized map. The local accuracy and variability of the segmentation algorithm at each point can be quantified by the average of these metrics for the whole group of subjects and visualized on the 2D standardized map. Based on the results shown on the 2D standardized map, a variety of strategies, such as adding anchor points and adjusting weights of different forces in the algorithm, can be introduced to improve the accuracy and variability of the algorithm. (paper)

Three Dimensional Fluorescence Microscopy Image Synthesis and Segmentation

OpenAIRE

Fu, Chichen; Lee, Soonam; Ho, David Joon; Han, Shuo; Salama, Paul; Dunn, Kenneth W.; Delp, Edward J.

2018-01-01

Advances in fluorescence microscopy enable acquisition of 3D image volumes with better image quality and deeper penetration into tissue. Segmentation is a required step to characterize and analyze biological structures in the images and recent 3D segmentation using deep learning has achieved promising results. One issue is that deep learning techniques require a large set of groundtruth data which is impractical to annotate manually for large 3D microscopy volumes. This paper describes a 3D d...

Multi-modal RGB–Depth–Thermal Human Body Segmentation

DEFF Research Database (Denmark)

Palmero, Cristina; Clapés, Albert; Bahnsen, Chris

2016-01-01

This work addresses the problem of human body segmentation from multi-modal visual cues as a first stage of automatic human behavior analysis. We propose a novel RGB-Depth-Thermal dataset along with a multi-modal seg- mentation baseline. The several modalities are registered us- ing a calibration...... to other state-of-the-art meth- ods, obtaining an overlap above 75% on the novel dataset when compared to the manually annotated ground-truth of human segmentations....

Automatic segmentation of the choroid in enhanced depth imaging optical coherence tomography images.

Science.gov (United States)

Tian, Jing; Marziliano, Pina; Baskaran, Mani; Tun, Tin Aung; Aung, Tin

2013-03-01

Enhanced Depth Imaging (EDI) optical coherence tomography (OCT) provides high-definition cross-sectional images of the choroid in vivo, and hence is used in many clinical studies. However, the quantification of the choroid depends on the manual labelings of two boundaries, Bruch's membrane and the choroidal-scleral interface. This labeling process is tedious and subjective of inter-observer differences, hence, automatic segmentation of the choroid layer is highly desirable. In this paper, we present a fast and accurate algorithm that could segment the choroid automatically. Bruch's membrane is detected by searching the pixel with the biggest gradient value above the retinal pigment epithelium (RPE) and the choroidal-scleral interface is delineated by finding the shortest path of the graph formed by valley pixels using Dijkstra's algorithm. The experiments comparing automatic segmentation results with the manual labelings are conducted on 45 EDI-OCT images and the average of Dice's Coefficient is 90.5%, which shows good consistency of the algorithm with the manual labelings. The processing time for each image is about 1.25 seconds.

A transfer-learning approach to image segmentation across scanners by maximizing distribution similarity

DEFF Research Database (Denmark)

van Opbroek, Annegreet; Ikram, M. Arfan; Vernooij, Meike W.

2013-01-01

Many successful methods for biomedical image segmentation are based on supervised learning, where a segmentation algorithm is trained based on manually labeled training data. For supervised-learning algorithms to perform well, this training data has to be representative for the target data. In pr...

WE-EF-210-08: BEST IN PHYSICS (IMAGING): 3D Prostate Segmentation in Ultrasound Images Using Patch-Based Anatomical Feature

Energy Technology Data Exchange (ETDEWEB)

Yang, X; Rossi, P; Jani, A; Ogunleye, T; Curran, W; Liu, T [Emory Univ, Atlanta, GA (United States)

2015-06-15

Purpose: Transrectal ultrasound (TRUS) is the standard imaging modality for the image-guided prostate-cancer interventions (e.g., biopsy and brachytherapy) due to its versatility and real-time capability. Accurate segmentation of the prostate plays a key role in biopsy needle placement, treatment planning, and motion monitoring. As ultrasound images have a relatively low signal-to-noise ratio (SNR), automatic segmentation of the prostate is difficult. However, manual segmentation during biopsy or radiation therapy can be time consuming. We are developing an automated method to address this technical challenge. Methods: The proposed segmentation method consists of two major stages: the training stage and the segmentation stage. During the training stage, patch-based anatomical features are extracted from the registered training images with patient-specific information, because these training images have been mapped to the new patient’ images, and the more informative anatomical features are selected to train the kernel support vector machine (KSVM). During the segmentation stage, the selected anatomical features are extracted from newly acquired image as the input of the well-trained KSVM and the output of this trained KSVM is the segmented prostate of this patient. Results: This segmentation technique was validated with a clinical study of 10 patients. The accuracy of our approach was assessed using the manual segmentation. The mean volume Dice Overlap Coefficient was 89.7±2.3%, and the average surface distance was 1.52 ± 0.57 mm between our and manual segmentation, which indicate that the automatic segmentation method works well and could be used for 3D ultrasound-guided prostate intervention. Conclusion: We have developed a new prostate segmentation approach based on the optimal feature learning framework, demonstrated its clinical feasibility, and validated its accuracy with manual segmentation (gold standard). This segmentation technique could be a useful

The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)

DEFF Research Database (Denmark)

Menze, Bjoern H.; Jakab, Andras; Bauer, Stefan

2015-01-01

a hierarchical majority vote yielded segmentations that consistently ranked above all individual algorithms, indicating remaining opportunities for further methodological improvements. The BRATS image data and manual annotations continue to be publicly available through an online evaluation system as an ongoing...

Highway Safety Manual applied in Missouri - freeway/software : research summary.

Science.gov (United States)

2016-03-01

AASHTOs Highway Safety Manual (HSM) : includes models for freeway segments, speedchange : lanes (transitional area between mainline : and ramps), ramps, and interchange terminals. : These predictive models for freeway : interchanges need to be cal...

Topological leakage detection and freeze-and-grow propagation for improved CT-based airway segmentation

Science.gov (United States)

Nadeem, Syed Ahmed; Hoffman, Eric A.; Sieren, Jered P.; Saha, Punam K.

2018-03-01

Numerous large multi-center studies are incorporating the use of computed tomography (CT)-based characterization of the lung parenchyma and bronchial tree to understand chronic obstructive pulmonary disease status and progression. To the best of our knowledge, there are no fully automated airway tree segmentation methods, free of the need for user review. A failure in even a fraction of segmentation results necessitates manual revision of all segmentation masks which is laborious considering the thousands of image data sets evaluated in large studies. In this paper, we present a novel CT-based airway tree segmentation algorithm using topological leakage detection and freeze-and-grow propagation. The method is fully automated requiring no manual inputs or post-segmentation editing. It uses simple intensity-based connectivity and a freeze-and-grow propagation algorithm to iteratively grow the airway tree starting from an initial seed inside the trachea. It begins with a conservative parameter and then, gradually shifts toward more generous parameter values. The method was applied on chest CT scans of fifteen subjects at total lung capacity. Airway segmentation results were qualitatively assessed and performed comparably to established airway segmentation method with no major visual leakages.

Segmentation of pomegranate MR images using spatial fuzzy c-means (SFCM) algorithm

Science.gov (United States)

Moradi, Ghobad; Shamsi, Mousa; Sedaaghi, M. H.; Alsharif, M. R.

2011-10-01

Segmentation is one of the fundamental issues of image processing and machine vision. It plays a prominent role in a variety of image processing applications. In this paper, one of the most important applications of image processing in MRI segmentation of pomegranate is explored. Pomegranate is a fruit with pharmacological properties such as being anti-viral and anti-cancer. Having a high quality product in hand would be critical factor in its marketing. The internal quality of the product is comprehensively important in the sorting process. The determination of qualitative features cannot be manually made. Therefore, the segmentation of the internal structures of the fruit needs to be performed as accurately as possible in presence of noise. Fuzzy c-means (FCM) algorithm is noise-sensitive and pixels with noise are classified inversely. As a solution, in this paper, the spatial FCM algorithm in pomegranate MR images' segmentation is proposed. The algorithm is performed with setting the spatial neighborhood information in FCM and modification of fuzzy membership function for each class. The segmentation algorithm results on the original and the corrupted Pomegranate MR images by Gaussian, Salt Pepper and Speckle noises show that the SFCM algorithm operates much more significantly than FCM algorithm. Also, after diverse steps of qualitative and quantitative analysis, we have concluded that the SFCM algorithm with 5×5 window size is better than the other windows.

The use of atlas registration and graph cuts for prostate segmentation in magnetic resonance images

Energy Technology Data Exchange (ETDEWEB)

Korsager, Anne Sofie, E-mail: asko@hst.aau.dk; Østergaard, Lasse Riis [Department of Health Science and Technology, Aalborg University, Aalborg 9220 (Denmark); Fortunati, Valerio; Lijn, Fedde van der; Niessen, Wiro; Walsum, Theo van [Biomedical Imaging Group of Rotterdam, Department of Medical Informatics and Radiology, Erasmus MC, Rotterdam 3015 GE Rotterdam (Netherlands); Carl, Jesper [Department of Medical Physics, Oncology, Aalborg University Hospital, Aalborg 9220 (Denmark)

2015-04-15

Purpose: An automatic method for 3D prostate segmentation in magnetic resonance (MR) images is presented for planning image-guided radiotherapy treatment of prostate cancer. Methods: A spatial prior based on intersubject atlas registration is combined with organ-specific intensity information in a graph cut segmentation framework. The segmentation is tested on 67 axial T{sub 2}-weighted MR images in a leave-one-out cross validation experiment and compared with both manual reference segmentations and with multiatlas-based segmentations using majority voting atlas fusion. The impact of atlas selection is investigated in both the traditional atlas-based segmentation and the new graph cut method that combines atlas and intensity information in order to improve the segmentation accuracy. Best results were achieved using the method that combines intensity information, shape information, and atlas selection in the graph cut framework. Results: A mean Dice similarity coefficient (DSC) of 0.88 and a mean surface distance (MSD) of 1.45 mm with respect to the manual delineation were achieved. Conclusions: This approaches the interobserver DSC of 0.90 and interobserver MSD 0f 1.15 mm and is comparable to other studies performing prostate segmentation in MR.

Intensity-based hierarchical clustering in CT-scans: application to interactive segmentation in cardiology

Science.gov (United States)

Hadida, Jonathan; Desrosiers, Christian; Duong, Luc

2011-03-01

The segmentation of anatomical structures in Computed Tomography Angiography (CTA) is a pre-operative task useful in image guided surgery. Even though very robust and precise methods have been developed to help achieving a reliable segmentation (level sets, active contours, etc), it remains very time consuming both in terms of manual interactions and in terms of computation time. The goal of this study is to present a fast method to find coarse anatomical structures in CTA with few parameters, based on hierarchical clustering. The algorithm is organized as follows: first, a fast non-parametric histogram clustering method is proposed to compute a piecewise constant mask. A second step then indexes all the space-connected regions in the piecewise constant mask. Finally, a hierarchical clustering is achieved to build a graph representing the connections between the various regions in the piecewise constant mask. This step builds up a structural knowledge about the image. Several interactive features for segmentation are presented, for instance association or disassociation of anatomical structures. A comparison with the Mean-Shift algorithm is presented.

Accuracy Assessment Measures for Image Segmentation Goodness of the Land Parcel Identification System

DEFF Research Database (Denmark)

Montaghi, Alessandro; Larsen, Rene; Greve, Mogens Humlekrog

2013-01-01

, was employed in order to assess the quality of segmentation. An accuracy assessment was performed using seven metrics based on the topological or geometric similarity between segmented polygons and reference polygons, which were derived through manual delineation. The results indicate that (1) segmentation...... accuracy is influenced by the size of the reference polygons and (2) the presence of clear boundaries (e.g. hedgerow, ponds, ditches and road) drives the segmentation algorithm when the scale parameter exceeds a certain value....

Segmentation of corpus callosum using diffusion tensor imaging: validation in patients with glioblastoma

International Nuclear Information System (INIS)

Nazem-Zadeh, Mohammad-Reza; Saksena, Sona; Babajani-Fermi, Abbas; Jiang, Quan; Soltanian-Zadeh, Hamid; Rosenblum, Mark; Mikkelsen, Tom; Jain, Rajan

2012-01-01

This paper presents a three-dimensional (3D) method for segmenting corpus callosum in normal subjects and brain cancer patients with glioblastoma. Nineteen patients with histologically confirmed treatment naïve glioblastoma and eleven normal control subjects underwent DTI on a 3T scanner. Based on the information inherent in diffusion tensors, a similarity measure was proposed and used in the proposed algorithm. In this algorithm, diffusion pattern of corpus callosum was used as prior information. Subsequently, corpus callosum was automatically divided into Witelson subdivisions. We simulated the potential rotation of corpus callosum under tumor pressure and studied the reproducibility of the proposed segmentation method in such cases. Dice coefficients, estimated to compare automatic and manual segmentation results for Witelson subdivisions, ranged from 94% to 98% for control subjects and from 81% to 95% for tumor patients, illustrating closeness of automatic and manual segmentations. Studying the effect of corpus callosum rotation by different Euler angles showed that although segmentation results were more sensitive to azimuth and elevation than skew, rotations caused by brain tumors do not have major effects on the segmentation results. The proposed method and similarity measure segment corpus callosum by propagating a hyper-surface inside the structure (resulting in high sensitivity), without penetrating into neighboring fiber bundles (resulting in high specificity)

Segmentation of breast ultrasound images based on active contours using neutrosophic theory.

Science.gov (United States)

Lotfollahi, Mahsa; Gity, Masoumeh; Ye, Jing Yong; Mahlooji Far, A

2018-04-01

Ultrasound imaging is an effective approach for diagnosing breast cancer, but it is highly operator-dependent. Recent advances in computer-aided diagnosis have suggested that it can assist physicians in diagnosis. Definition of the region of interest before computer analysis is still needed. Since manual outlining of the tumor contour is tedious and time-consuming for a physician, developing an automatic segmentation method is important for clinical application. The present paper represents a novel method to segment breast ultrasound images. It utilizes a combination of region-based active contour and neutrosophic theory to overcome the natural properties of ultrasound images including speckle noise and tissue-related textures. First, due to inherent speckle noise and low contrast of these images, we have utilized a non-local means filter and fuzzy logic method for denoising and image enhancement, respectively. This paper presents an improved weighted region-scalable active contour to segment breast ultrasound images using a new feature derived from neutrosophic theory. This method has been applied to 36 breast ultrasound images. It generates true-positive and false-positive results, and similarity of 95%, 6%, and 90%, respectively. The purposed method indicates clear advantages over other conventional methods of active contour segmentation, i.e., region-scalable fitting energy and weighted region-scalable fitting energy.

Typing operations manual and disposal of fixed assets: directions of improvement of accounting

Directory of Open Access Journals (Sweden)

I.M. Vygivska

2016-09-01

Full Text Available The lack of studies on the structure of business operations for the operation and disposal of fixed assets leads to undeveloped organizational and methodological provisions of the relevant accounting operations. In particular, the lack of comprehensive understanding of these operations can not account for the loss of alternatives and economic benefits from the use of fixed assets in various areas of economic activity. To streamline the organizational and methodological approaches to accounting of fixed assets, and monitor the effectiveness of the use and preservation of the property of the owner of the enterprise, and according to the analysis of literary sources showing a considerable amount of controversy in the existing approach of the authors, to characterize the operations manual and the disposal of fixed assets, the article suggests typing operations, exploitation and disposal of fixed assets. The main types of these operations include: 1 operation – storage, use, maintenance, repair and improvement; 2 disposal - sale, free transfer, exchange, cancellation due to moral and physical deterioration, capital contribution, financial lease, the installation of shortage, the transfer in payment of debt, the loss resulting from emergencies.

Segmentation of multiple sclerosis lesions in MR images: a review

International Nuclear Information System (INIS)

Mortazavi, Daryoush; Kouzani, Abbas Z.; Soltanian-Zadeh, Hamid

2012-01-01

Multiple sclerosis (MS) is an inflammatory demyelinating disease that the parts of the nervous system through the lesions generated in the white matter of the brain. It brings about disabilities in different organs of the body such as eyes and muscles. Early detection of MS and estimation of its progression are critical for optimal treatment of the disease. For diagnosis and treatment evaluation of MS lesions, they may be detected and segmented in Magnetic Resonance Imaging (MRI) scans of the brain. However, due to the large amount of MRI data to be analyzed, manual segmentation of the lesions by clinical experts translates into a very cumbersome and time consuming task. In addition, manual segmentation is subjective and prone to human errors. Several groups have developed computerized methods to detect and segment MS lesions. These methods are not categorized and compared in the past. This paper reviews and compares various MS lesion segmentation methods proposed in recent years. It covers conventional methods like multilevel thresholding and region growing, as well as more recent Bayesian methods that require parameter estimation algorithms. It also covers parameter estimation methods like expectation maximization and adaptive mixture model which are among unsupervised techniques as well as kNN and Parzen window methods that are among supervised techniques. Integration of knowledge-based methods such as atlas-based approaches with Bayesian methods increases segmentation accuracy. In addition, employing intelligent classifiers like Fuzzy C-Means, Fuzzy Inference Systems, and Artificial Neural Networks reduces misclassified voxels. (orig.)

IBES: A Tool for Creating Instructions Based on Event Segmentation

Directory of Open Access Journals (Sweden)

Katharina eMura

2013-12-01

Full Text Available Receiving informative, well-structured, and well-designed instructions supports performance and memory in assembly tasks. We describe IBES, a tool with which users can quickly and easily create multimedia, step-by-step instructions by segmenting a video of a task into segments. In a validation study we demonstrate that the step-by-step structure of the visual instructions created by the tool corresponds to the natural event boundaries, which are assessed by event segmentation and are known to play an important role in memory processes. In one part of the study, twenty participants created instructions based on videos of two different scenarios by using the proposed tool. In the other part of the study, ten and twelve participants respectively segmented videos of the same scenarios yielding event boundaries for coarse and fine events. We found that the visual steps chosen by the participants for creating the instruction manual had corresponding events in the event segmentation. The number of instructional steps was a compromise between the number of fine and coarse events. Our interpretation of results is that the tool picks up on natural human event perception processes of segmenting an ongoing activity into events and enables the convenient transfer into meaningful multimedia instructions for assembly tasks. We discuss the practical application of IBES, for example, creating manuals for differing expertise levels, and give suggestions for research on user-oriented instructional design based on this tool.

IBES: a tool for creating instructions based on event segmentation.

Science.gov (United States)

Mura, Katharina; Petersen, Nils; Huff, Markus; Ghose, Tandra

2013-12-26

Receiving informative, well-structured, and well-designed instructions supports performance and memory in assembly tasks. We describe IBES, a tool with which users can quickly and easily create multimedia, step-by-step instructions by segmenting a video of a task into segments. In a validation study we demonstrate that the step-by-step structure of the visual instructions created by the tool corresponds to the natural event boundaries, which are assessed by event segmentation and are known to play an important role in memory processes. In one part of the study, 20 participants created instructions based on videos of two different scenarios by using the proposed tool. In the other part of the study, 10 and 12 participants respectively segmented videos of the same scenarios yielding event boundaries for coarse and fine events. We found that the visual steps chosen by the participants for creating the instruction manual had corresponding events in the event segmentation. The number of instructional steps was a compromise between the number of fine and coarse events. Our interpretation of results is that the tool picks up on natural human event perception processes of segmenting an ongoing activity into events and enables the convenient transfer into meaningful multimedia instructions for assembly tasks. We discuss the practical application of IBES, for example, creating manuals for differing expertise levels, and give suggestions for research on user-oriented instructional design based on this tool.

Segmentation of multiple sclerosis lesions in MR images: a review

Energy Technology Data Exchange (ETDEWEB)

Mortazavi, Daryoush; Kouzani, Abbas Z. [Deakin University, School of Engineering, Geelong, Victoria (Australia); Soltanian-Zadeh, Hamid [Henry Ford Health System, Image Analysis Laboratory, Radiology Department, Detroit, MI (United States); University of Tehran, Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, Tehran (Iran, Islamic Republic of); School of Cognitive Sciences, Institute for Studies in Theoretical Physics and Mathematics (IPM), Tehran (Iran, Islamic Republic of)

2012-04-15

Multiple sclerosis (MS) is an inflammatory demyelinating disease that the parts of the nervous system through the lesions generated in the white matter of the brain. It brings about disabilities in different organs of the body such as eyes and muscles. Early detection of MS and estimation of its progression are critical for optimal treatment of the disease. For diagnosis and treatment evaluation of MS lesions, they may be detected and segmented in Magnetic Resonance Imaging (MRI) scans of the brain. However, due to the large amount of MRI data to be analyzed, manual segmentation of the lesions by clinical experts translates into a very cumbersome and time consuming task. In addition, manual segmentation is subjective and prone to human errors. Several groups have developed computerized methods to detect and segment MS lesions. These methods are not categorized and compared in the past. This paper reviews and compares various MS lesion segmentation methods proposed in recent years. It covers conventional methods like multilevel thresholding and region growing, as well as more recent Bayesian methods that require parameter estimation algorithms. It also covers parameter estimation methods like expectation maximization and adaptive mixture model which are among unsupervised techniques as well as kNN and Parzen window methods that are among supervised techniques. Integration of knowledge-based methods such as atlas-based approaches with Bayesian methods increases segmentation accuracy. In addition, employing intelligent classifiers like Fuzzy C-Means, Fuzzy Inference Systems, and Artificial Neural Networks reduces misclassified voxels. (orig.)

Segmentation of lung fields using Chan-Vese active contour model in chest radiographs

Science.gov (United States)

Sohn, Kiwon

2011-03-01

A CAD tool for chest radiographs consists of several procedures and the very first step is segmentation of lung fields. We develop a novel methodology for segmentation of lung fields in chest radiographs that can satisfy the following two requirements. First, we aim to develop a segmentation method that does not need a training stage with manual estimation of anatomical features in a large training dataset of images. Secondly, for the ease of implementation, it is desirable to apply a well established model that is widely used for various image-partitioning practices. The Chan-Vese active contour model, which is based on Mumford-Shah functional in the level set framework, is applied for segmentation of lung fields. With the use of this model, segmentation of lung fields can be carried out without detailed prior knowledge on the radiographic anatomy of the chest, yet in some chest radiographs, the trachea regions are unfavorably segmented out in addition to the lung field contours. To eliminate artifacts from the trachea, we locate the upper end of the trachea, find a vertical center line of the trachea and delineate it, and then brighten the trachea region to make it less distinctive. The segmentation process is finalized by subsequent morphological operations. We randomly select 30 images from the Japanese Society of Radiological Technology image database to test the proposed methodology and the results are shown. We hope our segmentation technique can help to promote of CAD tools, especially for emerging chest radiographic imaging techniques such as dual energy radiography and chest tomosynthesis.

Statistics-based segmentation using a continuous-scale naive Bayes approach

DEFF Research Database (Denmark)

Laursen, Morten Stigaard; Midtiby, Henrik Skov; Kruger, Norbert

2014-01-01

Segmentation is a popular preprocessing stage in the field of machine vision. In agricultural applications it can be used to distinguish between living plant material and soil in images. The normalized difference vegetation index (NDVI) and excess green (ExG) color features are often used...... segmentation over the normalized vegetation difference index and excess green. The inputs to this color feature are the R, G, B, and near-infrared color wells, their chromaticities, and NDVI, ExG, and excess red. We apply the developed technique to a dataset consisting of 20 manually segmented images captured...

REBA experimenters' manual

International Nuclear Information System (INIS)

Schuch, R.L.

1977-04-01

The REBA is a high-energy, pulsed electron beam or bremsstrahlung x-ray generator whose operational purpose is to provide an energy source of short duration for conducting experiments, primarily to determine material responses to rapid surface and in-depth deposition of energy. The purpose of this manual is to serve as a basic source of information for prospective users of REBA. Included is a brief discussion of the design and operation of the facility as well as a summary of output characteristics for electron beam modes and environmental data for x-ray operation. The manual also contains a description of the REBA experimental facilities, including geometry of the test cell, instrumentation and data collection capabilities, and services and support available to experimenters

Motor carrier industry profile study : financial and operating performance profiles by industry segment, 2001-2002.

Science.gov (United States)

2004-09-01

This report profiles the motor carrier industry and its significant operating segments. It is one of a series of reports analyzing various aspects of the motor carrier industry. Other reports in the series focus on the safety performance of the indus...

Application work risk of manual material handling operators using different lifting methods

Science.gov (United States)

Anizar; Matondang, AR; Sibarani, JA

2018-02-01

This study observed the activity of lifting and moving crates containing bottles at a pallet station in a carbonated drink factory. The activity of moving crates, each weighing 15 kg, is performed by four operators using different methods. An operator manually moves 250 crates daily and often takes rest during working. This study aims to find the most efficient method, that is using the least energy, to move crates. The workload is assessed using the method of Cardiovascular Strain Load (CVL) and energy expenditure. Operators’ arterial pulse is measured for 1 minute right before they start working and after they finish working; this is done to obtain work arterial pulse and rest arterial pulse. The way operators lift crates is analyzed using biomechanics. It is found that fatigue is experienced by all operators, with the exception of the 3rd operator who has a %CVL number below 30%. He positions the pallet to be parallel to the conveyor, and then stand in between during the lifting process. He only rotates his body to move the crate from the conveyor onto the pallet, requiring only little energy. This is one of the reasons why the %CVL number is lower than the other operators.

14 CFR 121.141 - Airplane flight manual.

Science.gov (United States)

2010-01-01

... 14 Aeronautics and Space 3 2010-01-01 2010-01-01 false Airplane flight manual. 121.141 Section 121... REQUIREMENTS: DOMESTIC, FLAG, AND SUPPLEMENTAL OPERATIONS Manual Requirements § 121.141 Airplane flight manual. (a) Each certificate holder shall keep a current approved airplane flight manual for each type of...

Operation and maintenance manual for the temporary septic holding tank at the 100-D remedial action support facility. Revision 1

International Nuclear Information System (INIS)

Kelty, G.G.

1996-09-01

This manual provides detailed information for the operation and maintenance of the sanitary wastewater holding system at the 100-D Remedial Action Support Facility located in the 100-DR-1 Operable Unit of the Hanford Site. This document describes operations, including the type and frequency of required maintenance, and system failure response procedures

Clinical Evaluation of a Fully-automatic Segmentation Method for Longitudinal Brain Tumor Volumetry

Science.gov (United States)

Meier, Raphael; Knecht, Urspeter; Loosli, Tina; Bauer, Stefan; Slotboom, Johannes; Wiest, Roland; Reyes, Mauricio

2016-03-01

Information about the size of a tumor and its temporal evolution is needed for diagnosis as well as treatment of brain tumor patients. The aim of the study was to investigate the potential of a fully-automatic segmentation method, called BraTumIA, for longitudinal brain tumor volumetry by comparing the automatically estimated volumes with ground truth data acquired via manual segmentation. Longitudinal Magnetic Resonance (MR) Imaging data of 14 patients with newly diagnosed glioblastoma encompassing 64 MR acquisitions, ranging from preoperative up to 12 month follow-up images, was analysed. Manual segmentation was performed by two human raters. Strong correlations (R = 0.83-0.96, p < 0.001) were observed between volumetric estimates of BraTumIA and of each of the human raters for the contrast-enhancing (CET) and non-enhancing T2-hyperintense tumor compartments (NCE-T2). A quantitative analysis of the inter-rater disagreement showed that the disagreement between BraTumIA and each of the human raters was comparable to the disagreement between the human raters. In summary, BraTumIA generated volumetric trend curves of contrast-enhancing and non-enhancing T2-hyperintense tumor compartments comparable to estimates of human raters. These findings suggest the potential of automated longitudinal tumor segmentation to substitute manual volumetric follow-up of contrast-enhancing and non-enhancing T2-hyperintense tumor compartments.

Light-water-reactor hydrogen manual

International Nuclear Information System (INIS)

Camp, A.L.; Cummings, J.C.; Sherman, M.P.; Kupiec, C.F.; Healy, R.J.; Caplan, J.S.; Sandhop, J.R.; Saunders, J.H.

1983-06-01

A manual concerning the behavior of hydrogen in light water reactors has been prepared. Both normal operations and accident situations are addressed. Topics considered include hydrogen generation, transport and mixing, detection, and combustion, and mitigation. Basic physical and chemical phenomena are described, and plant-specific examples are provided where appropriate. A wide variety of readers, including operators, designers, and NRC staff, will find parts of this manual useful. Different sections are written at different levels, according to the most likely audience. The manual is not intended to provide specific plant procedures, but rather, to provide general guidance that may assist in the development of such procedures

Analysis on Biomechanical Characteristics of Post-operational Vertebral C5-C6 Segments

Directory of Open Access Journals (Sweden)

Heqiang Tian

2016-03-01

Full Text Available Both anterior cervical decompression and fusion (ACDF and artificial cervical disc replacement (ACDR have obvious advantages in the treatment of cervical spondylosis. To analyze the operation results, it is absolutely necessary to study the biomechanics of the movement range of post-operational vertebral C5-C6 segments, especially the biomechanical characteristics in cervical tissues in actual movements. In this study, using the human vertebral 3D graph gained by imaging diagnosis (CT, a vertebral solid model is established by the 3D reconstruction algorithm and reverse engineering technology. After that, with cervical soft tissue structure added to the solid model and set with a joint contact mechanism, a finite element model with a complete, accurate cervical C5-C6 kinematic unit is constructed, based on relevant physiological anatomical knowledge. This model includes vertebral segments, an intervertebral disc, ligament and zygopophysis in the cervical C5-C6 kinematic unit. In the created vertebral finite element model, the model is amended, referring to ACDF and ACDR, and the load and constraint are applied to a normal group, a fusion group and a displacement group, so as to analyze the biomechanical characteristics of the cervical vertebra after ACDF and ACDR. By comparing the finite element simulation results of different surgeries, this paper is intended to evaluate the functions and biomechanical behaviors of the post-operational vertebra, and explore the influence of the operation on the biomechanical stability of the cervical vertebra. This will provide theoretical guidance for implementation and optimization of ACDF and ACDR.

Segmentation of tumor ultrasound image in HIFU therapy based on texture and boundary encoding

International Nuclear Information System (INIS)

Zhang, Dong; Xu, Menglong; Quan, Long; Yang, Yan; Qin, Qianqing; Zhu, Wenbin

2015-01-01

It is crucial in high intensity focused ultrasound (HIFU) therapy to detect the tumor precisely with less manual intervention for enhancing the therapy efficiency. Ultrasound image segmentation becomes a difficult task due to signal attenuation, speckle effect and shadows. This paper presents an unsupervised approach based on texture and boundary encoding customized for ultrasound image segmentation in HIFU therapy. The approach oversegments the ultrasound image into some small regions, which are merged by using the principle of minimum description length (MDL) afterwards. Small regions belonging to the same tumor are clustered as they preserve similar texture features. The mergence is completed by obtaining the shortest coding length from encoding textures and boundaries of these regions in the clustering process. The tumor region is finally selected from merged regions by a proposed algorithm without manual interaction. The performance of the method is tested on 50 uterine fibroid ultrasound images from HIFU guiding transducers. The segmentations are compared with manual delineations to verify its feasibility. The quantitative evaluation with HIFU images shows that the mean true positive of the approach is 93.53%, the mean false positive is 4.06%, the mean similarity is 89.92%, the mean norm Hausdorff distance is 3.62% and the mean norm maximum average distance is 0.57%. The experiments validate that the proposed method can achieve favorable segmentation without manual initialization and effectively handle the poor quality of the ultrasound guidance image in HIFU therapy, which indicates that the approach is applicable in HIFU therapy. (paper)

Operating manual for the emission spectrometer NOI-6e for laboratory use; Manual de operacion de manejo del espectrometro de emision NOI-6e para uso de laboratorio

Energy Technology Data Exchange (ETDEWEB)

Albornoz G, M P

1993-08-01

This manual describes graphically and specifically how to operate the Emission Spectrometer NOI-6e. Detailed instructions are given for everything form turning on the equipment, quality control of several parameters, calibration, sample analysis; measurements and obtaining final results form the microprocessors. (author).

Radar and ARPA manual

CERN Document Server

Bole, A G

2013-01-01

Radar and ARPA Manual focuses on the theoretical and practical aspects of electronic navigation. The manual first discusses basic radar principles, including principles of range and bearing measurements and picture orientation and presentation. The text then looks at the operational principles of radar systems. Function of units; aerial, receiver, and display principles; transmitter principles; and sitting of units on board ships are discussed. The book also describes target detection, Automatic Radar Plotting Aids (ARPA), and operational controls of radar systems, and then discusses radar plo

Fully automatic registration and segmentation of first-pass myocardial perfusion MR image sequences.

Science.gov (United States)

Gupta, Vikas; Hendriks, Emile A; Milles, Julien; van der Geest, Rob J; Jerosch-Herold, Michael; Reiber, Johan H C; Lelieveldt, Boudewijn P F

2010-11-01

Derivation of diagnostically relevant parameters from first-pass myocardial perfusion magnetic resonance images involves the tedious and time-consuming manual segmentation of the myocardium in a large number of images. To reduce the manual interaction and expedite the perfusion analysis, we propose an automatic registration and segmentation method for the derivation of perfusion linked parameters. A complete automation was accomplished by first registering misaligned images using a method based on independent component analysis, and then using the registered data to automatically segment the myocardium with active appearance models. We used 18 perfusion studies (100 images per study) for validation in which the automatically obtained (AO) contours were compared with expert drawn contours on the basis of point-to-curve error, Dice index, and relative perfusion upslope in the myocardium. Visual inspection revealed successful segmentation in 15 out of 18 studies. Comparison of the AO contours with expert drawn contours yielded 2.23 ± 0.53 mm and 0.91 ± 0.02 as point-to-curve error and Dice index, respectively. The average difference between manually and automatically obtained relative upslope parameters was found to be statistically insignificant (P = .37). Moreover, the analysis time per slice was reduced from 20 minutes (manual) to 1.5 minutes (automatic). We proposed an automatic method that significantly reduced the time required for analysis of first-pass cardiac magnetic resonance perfusion images. The robustness and accuracy of the proposed method were demonstrated by the high spatial correspondence and statistically insignificant difference in perfusion parameters, when AO contours were compared with expert drawn contours. Copyright © 2010 AUR. Published by Elsevier Inc. All rights reserved.

Fluid region segmentation in OCT images based on convolution neural network

Science.gov (United States)

Liu, Dong; Liu, Xiaoming; Fu, Tianyu; Yang, Zhou

2017-07-01

In the retinal image, characteristics of fluid have great significance for diagnosis in eye disease. In the clinical, the segmentation of fluid is usually conducted manually, but is time-consuming and the accuracy is highly depend on the expert's experience. In this paper, we proposed a segmentation method based on convolution neural network (CNN) for segmenting the fluid from fundus image. The B-scans of OCT are segmented into layers, and patches from specific region with annotation are used for training. After the data set being divided into training set and test set, network training is performed and a good segmentation result is obtained, which has a significant advantage over traditional methods such as threshold method.

Operations Manual for Incident and Emergency Communication. Date Effective: 1 June 2012 (Spanish Edition)

International Nuclear Information System (INIS)

2012-01-01

The Convention on Early Notification of a Nuclear Accident (the 'Early Notification Convention') and the Convention on Assistance in the Case of a Nuclear Accident or Radiological Emergency (the 'Assistance Convention') are the prime legal instruments that establish an international framework to facilitate the exchange of information and the prompt provision of assistance in the event of a nuclear or radiological incident or emergency, with the aim of minimizing the consequences. The International Atomic Energy Agency (IAEA) has specific functions assigned to it under these Conventions. The arrangements provided between the IAEA, the IAEA's Member States and/or Parties to one or both Conventions, all other relevant international intergovernmental organizations (herein referred to as international organizations), and other States for facilitating the implementation of these Conventions - specifically concerning those articles that are operational in nature - are documented in the present Operations Manual for Incident and Emergency Communication (IEComm). IEComm is the successor to the previous Emergency Notification and Assistance Technical Operations Manual (ENATOM), first issued on 18 January 1989. Member States, Parties to the Early Notification and Assistance Conventions, relevant international organizations and other States, have since then regularly received updates to the manual. This manual covers the communication protocols for Contact Points identified under the Early Notification and Assistance Conventions, as well as the protocol for users of the International Nuclear and Radiological Event Scale (INES). Since the last edition of ENATOM, several factors have warranted some modifications to the existing arrangements: changes due to lessons identified from experience in exchanging information during incidents and emergencies, responding to requests for information and assistance during nuclear and radiological incidents and emergencies in the past few

Operations Manual for Incident and Emergency Communication. Date Effective: 1 June 2012 (Chinese Edition)

International Nuclear Information System (INIS)

2013-01-01

The Convention on Early Notification of a Nuclear Accident (the 'Early Notification Convention') and the Convention on Assistance in the Case of a Nuclear Accident or Radiological Emergency (the 'Assistance Convention') are the … prime legal instruments that establish an international framework to facilitate the exchange of information and the prompt provision of assistance in the event of a nuclear or radiological incident or emergency, with the aim of minimizing the consequences. The International Atomic Energy Agency (IAEA) has specific functions assigned to it under these Conventions. The arrangements provided between the IAEA, the IAEA's Member States and/or Parties to one or both Conventions, all other relevant international intergovernmental organizations (herein referred to as international organizations), and other States for facilitating the implementation of these Conventions - specifically concerning those articles that are operational in nature - are documented in the present Operations Manual for Incident and Emergency Communication (IEComm). IEComm is the successor to the previous Emergency Notification and Assistance Technical Operations Manual (ENATOM), first issued on 18 January 1989. Member States, Parties to the Early Notification and Assistance Conventions, relevant international organizations and other States, have since then regularly received updates to the manual. This manual covers the communication protocols for Contact Points identified under the Early Notification and Assistance Conventions, as well as the protocol for users of the International Nuclear and Radiological Event Scale (INES). Since the last edition of ENATOM, several factors have warranted some modifications to the existing arrangements: changes due to lessons identified from experience in exchanging information during incidents and emergencies, responding to requests for information and assistance during nuclear and radiological incidents and emergencies in the past few

Operations Manual for Incident and Emergency Communication. Date Effective: 1 June 2012 (Arabic Edition)

International Nuclear Information System (INIS)

2012-01-01

The Convention on Early Notification of a Nuclear Accident (the 'Early Notification Convention') and the Convention on Assistance in the Case of a Nuclear Accident or Radiological Emergency (the 'Assistance Convention') are the prime legal instruments that establish an international framework to facilitate the exchange of information and the prompt provision of assistance in the event of a nuclear or radiological incident or emergency, with the aim of minimizing the consequences. The International Atomic Energy Agency (IAEA) has specific functions assigned to it under these Conventions. The arrangements provided between the IAEA, the IAEA's Member States and/or Parties to one or both Conventions, all other relevant international intergovernmental organizations (herein referred to as international organizations), and other States for facilitating the implementation of these Conventions - specifically concerning those articles that are operational in nature - are documented in the present Operations Manual for Incident and Emergency Communication (IEComm). IEComm is the successor to the previous Emergency Notification and Assistance Technical Operations Manual (ENATOM), first issued on 18 January 1989. Member States, Parties to the Early Notification and Assistance Conventions, relevant international organizations and other States, have since then regularly received updates to the manual. This manual covers the communication protocols for Contact Points identified under the Early Notification and Assistance Conventions, as well as the protocol for users of the International Nuclear and Radiological Event Scale (INES). Since the last edition of ENATOM, several factors have warranted some modifications to the existing arrangements: changes due to lessons identified from experience in exchanging information during incidents and emergencies, responding to requests for information and assistance during nuclear and radiological incidents and emergencies in the past few

Epidermal segmentation in high-definition optical coherence tomography.

Science.gov (United States)

Li, Annan; Cheng, Jun; Yow, Ai Ping; Wall, Carolin; Wong, Damon Wing Kee; Tey, Hong Liang; Liu, Jiang

2015-01-01

Epidermis segmentation is a crucial step in many dermatological applications. Recently, high-definition optical coherence tomography (HD-OCT) has been developed and applied to imaging subsurface skin tissues. In this paper, a novel epidermis segmentation method using HD-OCT is proposed in which the epidermis is segmented by 3 steps: the weighted least square-based pre-processing, the graph-based skin surface detection and the local integral projection-based dermal-epidermal junction detection respectively. Using a dataset of five 3D volumes, we found that this method correlates well with the conventional method of manually marking out the epidermis. This method can therefore serve to effectively and rapidly delineate the epidermis for study and clinical management of skin diseases.

Fully automatic segmentation of arbitrarily shaped fiducial markers in cone-beam CT projections

DEFF Research Database (Denmark)

Bertholet, Jenny; Wan, Hanlin; Toftegaard, Jakob

2017-01-01

segmentation, the DPTB algorithm generates and uses a 3D marker model to create 2D templates at any projection angle. The 2D templates are used to segment the marker position as the position with highest normalized cross-correlation in a search area centered at the DP segmented position. The accuracy of the DP...... algorithm and the new DPTB algorithm was quantified as the 2D segmentation error (pixels) compared to a manual ground truth segmentation for 97 markers in the projection images of CBCT scans of 40 patients. Also the fraction of wrong segmentations, defined as 2D errors larger than 5 pixels, was calculated...

Techniques on semiautomatic segmentation using the Adobe Photoshop

Science.gov (United States)

Park, Jin Seo; Chung, Min Suk; Hwang, Sung Bae

2005-04-01

The purpose of this research is to enable anybody to semiautomatically segment the anatomical structures in the MRIs, CTs, and other medical images on the personal computer. The segmented images are used for making three-dimensional images, which are helpful in medical education and research. To achieve this purpose, the following trials were performed. The entire body of a volunteer was MR scanned to make 557 MRIs, which were transferred to a personal computer. On Adobe Photoshop, contours of 19 anatomical structures in the MRIs were semiautomatically drawn using MAGNETIC LASSO TOOL; successively, manually corrected using either LASSO TOOL or DIRECT SELECTION TOOL to make 557 segmented images. In a likewise manner, 11 anatomical structures in the 8,500 anatomcial images were segmented. Also, 12 brain and 10 heart anatomical structures in anatomical images were segmented. Proper segmentation was verified by making and examining the coronal, sagittal, and three-dimensional images from the segmented images. During semiautomatic segmentation on Adobe Photoshop, suitable algorithm could be used, the extent of automatization could be regulated, convenient user interface could be used, and software bugs rarely occurred. The techniques of semiautomatic segmentation using Adobe Photoshop are expected to be widely used for segmentation of the anatomical structures in various medical images.

Information to licensees regarding two NRC Inspection Manual sections on resolution of degraded and nonconforming conditions and on operability (Generic Letter 91-18)

International Nuclear Information System (INIS)

Partlow, J.G.

1992-01-01

The NRC staff has issued two sections to be included in Part 9900, Technical Guidance, of the NRC Inspection Manual. The first is, ''Resolution of Degraded and Nonconforming Conditions.'' The second is, ''Operable/Operability: Ensuring the Functional Capability of a System or Component.'' Copies of the additions to the NRC Inspection Manual are provided for information only. No specific licensee actions are required. The additions to the NRC Inspection Manual are based upon previously issued guidance. However, because of the complexity involved in operability determinations and the resolution of degraded and nonconforming conditions, there have been differences in application by NRC staff during past inspection activities. Thus, the purpose of publishing this guidance is to ensure consistency in application of this guidance by the NRC. Regional inspection personnel have been briefed on this guidance. The NRC will conduct further training on these topics to ensure uniform staff understanding

Hybrid Clustering And Boundary Value Refinement for Tumor Segmentation using Brain MRI

Science.gov (United States)

Gupta, Anjali; Pahuja, Gunjan

2017-08-01

The method of brain tumor segmentation is the separation of tumor area from Brain Magnetic Resonance (MR) images. There are number of methods already exist for segmentation of brain tumor efficiently. However it’s tedious task to identify the brain tumor from MR images. The segmentation process is extraction of different tumor tissues such as active, tumor, necrosis, and edema from the normal brain tissues such as gray matter (GM), white matter (WM), as well as cerebrospinal fluid (CSF). As per the survey study, most of time the brain tumors are detected easily from brain MR image using region based approach but required level of accuracy, abnormalities classification is not predictable. The segmentation of brain tumor consists of many stages. Manually segmenting the tumor from brain MR images is very time consuming hence there exist many challenges in manual segmentation. In this research paper, our main goal is to present the hybrid clustering which consists of Fuzzy C-Means Clustering (for accurate tumor detection) and level set method(for handling complex shapes) for the detection of exact shape of tumor in minimal computational time. using this approach we observe that for a certain set of images 0.9412 sec of time is taken to detect tumor which is very less in comparison to recent existing algorithm i.e. Hybrid clustering (Fuzzy C-Means and K Means clustering).

Operation and maintenance manual for the temporary septic holding tank at the 100-D remedial action support facility. Revision 2

International Nuclear Information System (INIS)

Kelty, G.G.

1996-10-01

This manual was prepared to provide detailed information for the operation and maintenance of the sanitary wastewater holding system at the 100-D Remedial Action Support Facility located in the 100-DR-1 Operable Unit at the Hanford Site. This document describes operations, including the type and frequency of required maintenance, and system failure response procedures

AFM-CMM integrated instrument user manual

DEFF Research Database (Denmark)

Marinello, Francesco; Bariani, Paolo

This manual gives general important guidelines for a proper use of the integrated AFM-CMM instrument. More information can be collected reading: • N. Kofod Ph.D thesis [1]; • P. Bariani Ph.D thesis [2]; • Dualscope DME 95-200 operation manuals [3]; • SPIP help [4] • Stitching software user manual...

Manual treatment effects to the upper cervical apophysial joints before, during, and after endotracheal anesthesia: a placebo-controlled comparison.

Science.gov (United States)

Buchmann, Johannes; Wende, Klaus; Kundt, Guenther; Haessler, Frank

2005-04-01

In this preliminary, placebo-controlled clinical trial, two different manual treatments were compared, spinal manipulation and postisometric relaxation, for dysfunctional motion segments of the upper cervical spinal column. The influence of the muscular portion on the joint-play restriction of a motion segment can be ignored in anesthesia, and the manual evaluation of this joint-play restriction must be focused on nonmuscular structures. By retesting in anesthesia, it is possible to examine whether mobilization and manipulation affect exclusively the muscular structures or also affect the other parts of the motion segment. Conclusions can be drawn about the superiority of one or both treatments and about the structural basis of the restricted joint play and its palpation. A total of 26 inpatients at the surgical or orthopedic department of the University of Rostock were examined manually at four testing times: before and after manual treatment, in anesthesia, and within 24 hrs of completing anesthesia. They were randomized into three groups: postisometric relaxation (mobilization), spinal manipulation (thrust technique), and placebo. A highly significant effect for both treatments was found posttherapeutically (P anesthesia, the treatment effect of spinal manipulation was further significant (P spinal manipulation and postisometric relaxation was not found in anesthesia (P = 0.137). The treatment effect postnarcotically was further significant when compared with placebo only for spinal manipulation (P = 0.011). Both treatments are superior to placebo. Postisometric relaxation seems to affect mainly the muscular parts of the treated segments and less so the other parts, such as the joint capsule or the segmental affiliated ligaments and fascia. Spinal manipulation seems to influence all other segmental parts more effectively, and the treatment effect persists longer. A joint-play restriction cannot be an exclusively muscular tension phenomenon. Segmental motion

Validation of phalanx bone three-dimensional surface segmentation from computed tomography images using laser scanning

International Nuclear Information System (INIS)

DeVries, Nicole A.; Gassman, Esther E.; Kallemeyn, Nicole A.; Shivanna, Kiran H.; Magnotta, Vincent A.; Grosland, Nicole M.

2008-01-01

To examine the validity of manually defined bony regions of interest from computed tomography (CT) scans. Segmentation measurements were performed on the coronal reformatted CT images of the three phalanx bones of the index finger from five cadaveric specimens. Two smoothing algorithms (image-based and Laplacian surface-based) were evaluated to determine their ability to represent accurately the anatomic surface. The resulting surfaces were compared with laser surface scans of the corresponding cadaveric specimen. The average relative overlap between two tracers was 0.91 for all bones. The overall mean difference between the manual unsmoothed surface and the laser surface scan was 0.20 mm. Both image-based and Laplacian surface-based smoothing were compared; the overall mean difference for image-based smoothing was 0.21 mm and 0.20 mm for Laplacian smoothing. This study showed that manual segmentation of high-contrast, coronal, reformatted, CT datasets can accurately represent the true surface geometry of bones. Additionally, smoothing techniques did not significantly alter the surface representations. This validation technique should be extended to other bones, image segmentation and spatial filtering techniques. (orig.)

Validation of phalanx bone three-dimensional surface segmentation from computed tomography images using laser scanning

Energy Technology Data Exchange (ETDEWEB)

DeVries, Nicole A.; Gassman, Esther E.; Kallemeyn, Nicole A. [The University of Iowa, Department of Biomedical Engineering, Center for Computer Aided Design, Iowa City, IA (United States); Shivanna, Kiran H. [The University of Iowa, Center for Computer Aided Design, Iowa City, IA (United States); Magnotta, Vincent A. [The University of Iowa, Department of Biomedical Engineering, Department of Radiology, Center for Computer Aided Design, Iowa City, IA (United States); Grosland, Nicole M. [The University of Iowa, Department of Biomedical Engineering, Department of Orthopaedics and Rehabilitation, Center for Computer Aided Design, Iowa City, IA (United States)

2008-01-15

To examine the validity of manually defined bony regions of interest from computed tomography (CT) scans. Segmentation measurements were performed on the coronal reformatted CT images of the three phalanx bones of the index finger from five cadaveric specimens. Two smoothing algorithms (image-based and Laplacian surface-based) were evaluated to determine their ability to represent accurately the anatomic surface. The resulting surfaces were compared with laser surface scans of the corresponding cadaveric specimen. The average relative overlap between two tracers was 0.91 for all bones. The overall mean difference between the manual unsmoothed surface and the laser surface scan was 0.20 mm. Both image-based and Laplacian surface-based smoothing were compared; the overall mean difference for image-based smoothing was 0.21 mm and 0.20 mm for Laplacian smoothing. This study showed that manual segmentation of high-contrast, coronal, reformatted, CT datasets can accurately represent the true surface geometry of bones. Additionally, smoothing techniques did not significantly alter the surface representations. This validation technique should be extended to other bones, image segmentation and spatial filtering techniques. (orig.)

Regulations and Procedures Manual

Energy Technology Data Exchange (ETDEWEB)

Young, Lydia [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

2010-09-30

The purpose of the Regulations and Procedures Manual (RPM) is to provide Laboratory personnel with a reference to University and Lawrence Berkeley National Laboratory policies and regulations by outlining the normal practices and answering most policy questions that arise in the day-to-day operations of Laboratory departments. Much of the information in this manual has been condensed from detail provided in Laboratory procedure manuals, Department of Energy (DOE) directives, and Contract DE-AC02-05CH11231. This manual is not intended, however, to replace any of those documents. The sections on personnel apply only to employees who are not represented by unions. Personnel policies pertaining to employees represented by unions may be found in their labor agreements. Questions concerning policy interpretation should be directed to the department responsible for the particular policy. A link to the Managers Responsible for RPM Sections is available on the RPM home page. If it is not clear which department should be called, please contact the Associate Laboratory Director of Operations.

Automatic segmentation of dynamic neuroreceptor single-photon emission tomography images using fuzzy clustering

International Nuclear Information System (INIS)

Acton, P.D.; Pilowsky, L.S.; Kung, H.F.; Ell, P.J.

1999-01-01

The segmentation of medical images is one of the most important steps in the analysis and quantification of imaging data. However, partial volume artefacts make accurate tissue boundary definition difficult, particularly for images with lower resolution commonly used in nuclear medicine. In single-photon emission tomography (SPET) neuroreceptor studies, areas of specific binding are usually delineated by manually drawing regions of interest (ROIs), a time-consuming and subjective process. This paper applies the technique of fuzzy c-means clustering (FCM) to automatically segment dynamic neuroreceptor SPET images. Fuzzy clustering was tested using a realistic, computer-generated, dynamic SPET phantom derived from segmenting an MR image of an anthropomorphic brain phantom. Also, the utility of applying FCM to real clinical data was assessed by comparison against conventional ROI analysis of iodine-123 iodobenzamide (IBZM) binding to dopamine D 2 /D 3 receptors in the brains of humans. In addition, a further test of the methodology was assessed by applying FCM segmentation to [ 123 I]IDAM images (5-iodo-2-[[2-2-[(dimethylamino)methyl]phenyl]thio] benzyl alcohol) of serotonin transporters in non-human primates. In the simulated dynamic SPET phantom, over a wide range of counts and ratios of specific binding to background, FCM correlated very strongly with the true counts (correlation coefficient r 2 >0.99, P 123 I]IBZM data comparable with manual ROI analysis, with the binding ratios derived from both methods significantly correlated (r 2 =0.83, P<0.0001). Fuzzy clustering is a powerful tool for the automatic, unsupervised segmentation of dynamic neuroreceptor SPET images. Where other automated techniques fail completely, and manual ROI definition would be highly subjective, FCM is capable of segmenting noisy images in a robust and repeatable manner. (orig.)

Wheat Ear Detection in Plots by Segmenting Mobile Laser Scanner Data

Science.gov (United States)

Velumani, K.; Oude Elberink, S.; Yang, M. Y.; Baret, F.

2017-09-01

The use of Light Detection and Ranging (LiDAR) to study agricultural crop traits is becoming popular. Wheat plant traits such as crop height, biomass fractions and plant population are of interest to agronomists and biologists for the assessment of a genotype's performance in the environment. Among these performance indicators, plant population in the field is still widely estimated through manual counting which is a tedious and labour intensive task. The goal of this study is to explore the suitability of LiDAR observations to automate the counting process by the individual detection of wheat ears in the agricultural field. However, this is a challenging task owing to the random cropping pattern and noisy returns present in the point cloud. The goal is achieved by first segmenting the 3D point cloud followed by the classification of segments into ears and non-ears. In this study, two segmentation techniques: a) voxel-based segmentation and b) mean shift segmentation were adapted to suit the segmentation of plant point clouds. An ear classification strategy was developed to distinguish the ear segments from leaves and stems. Finally, the ears extracted by the automatic methods were compared with reference ear segments prepared by manual segmentation. Both the methods had an average detection rate of 85 %, aggregated over different flowering stages. The voxel-based approach performed well for late flowering stages (wheat crops aged 210 days or more) with a mean percentage accuracy of 94 % and takes less than 20 seconds to process 50,000 points with an average point density of 16  points/cm2. Meanwhile, the mean shift approach showed comparatively better counting accuracy of 95% for early flowering stage (crops aged below 225 days) and takes approximately 4 minutes to process 50,000 points.

Supervised machine learning-based classification scheme to segment the brainstem on MRI in multicenter brain tumor treatment context.

Science.gov (United States)

Dolz, Jose; Laprie, Anne; Ken, Soléakhéna; Leroy, Henri-Arthur; Reyns, Nicolas; Massoptier, Laurent; Vermandel, Maximilien

2016-01-01

To constrain the risk of severe toxicity in radiotherapy and radiosurgery, precise volume delineation of organs at risk is required. This task is still manually performed, which is time-consuming and prone to observer variability. To address these issues, and as alternative to atlas-based segmentation methods, machine learning techniques, such as support vector machines (SVM), have been recently presented to segment subcortical structures on magnetic resonance images (MRI). SVM is proposed to segment the brainstem on MRI in multicenter brain cancer context. A dataset composed by 14 adult brain MRI scans is used to evaluate its performance. In addition to spatial and probabilistic information, five different image intensity values (IIVs) configurations are evaluated as features to train the SVM classifier. Segmentation accuracy is evaluated by computing the Dice similarity coefficient (DSC), absolute volumes difference (AVD) and percentage volume difference between automatic and manual contours. Mean DSC for all proposed IIVs configurations ranged from 0.89 to 0.90. Mean AVD values were below 1.5 cm(3), where the value for best performing IIVs configuration was 0.85 cm(3), representing an absolute mean difference of 3.99% with respect to the manual segmented volumes. Results suggest consistent volume estimation and high spatial similarity with respect to expert delineations. The proposed approach outperformed presented methods to segment the brainstem, not only in volume similarity metrics, but also in segmentation time. Preliminary results showed that the approach might be promising for adoption in clinical use.

Contour tracing for segmentation of mammographic masses

International Nuclear Information System (INIS)

Elter, Matthias; Held, Christian; Wittenberg, Thomas

2010-01-01

CADx systems have the potential to support radiologists in the difficult task of discriminating benign and malignant mammographic lesions. The segmentation of mammographic masses from the background tissue is an important module of CADx systems designed for the characterization of mass lesions. In this work, a novel approach to this task is presented. The segmentation is performed by automatically tracing the mass' contour in-between manually provided landmark points defined on the mass' margin. The performance of the proposed approach is compared to the performance of implementations of three state-of-the-art approaches based on region growing and dynamic programming. For an unbiased comparison of the different segmentation approaches, optimal parameters are selected for each approach by means of tenfold cross-validation and a genetic algorithm. Furthermore, segmentation performance is evaluated on a dataset of ROI and ground-truth pairs. The proposed method outperforms the three state-of-the-art methods. The benchmark dataset will be made available with publication of this paper and will be the first publicly available benchmark dataset for mass segmentation.

Development and Evaluation of a Semi-automated Segmentation Tool and a Modified Ellipsoid Formula for Volumetric Analysis of the Kidney in Non-contrast T2-Weighted MR Images.

Science.gov (United States)

Seuss, Hannes; Janka, Rolf; Prümmer, Marcus; Cavallaro, Alexander; Hammon, Rebecca; Theis, Ragnar; Sandmair, Martin; Amann, Kerstin; Bäuerle, Tobias; Uder, Michael; Hammon, Matthias

2017-04-01

Volumetric analysis of the kidney parenchyma provides additional information for the detection and monitoring of various renal diseases. Therefore the purposes of the study were to develop and evaluate a semi-automated segmentation tool and a modified ellipsoid formula for volumetric analysis of the kidney in non-contrast T2-weighted magnetic resonance (MR)-images. Three readers performed semi-automated segmentation of the total kidney volume (TKV) in axial, non-contrast-enhanced T2-weighted MR-images of 24 healthy volunteers (48 kidneys) twice. A semi-automated threshold-based segmentation tool was developed to segment the kidney parenchyma. Furthermore, the three readers measured renal dimensions (length, width, depth) and applied different formulas to calculate the TKV. Manual segmentation served as a reference volume. Volumes of the different methods were compared and time required was recorded. There was no significant difference between the semi-automatically and manually segmented TKV (p = 0.31). The difference in mean volumes was 0.3 ml (95% confidence interval (CI), -10.1 to 10.7 ml). Semi-automated segmentation was significantly faster than manual segmentation, with a mean difference = 188 s (220 vs. 408 s); p T2-weighted MR data delivers accurate and reproducible results and was significantly faster than manual segmentation. Applying a modified ellipsoid formula quickly provides an accurate kidney volume.

Microbial ecology laboratory procedures manual NASA/MSFC

Science.gov (United States)

Huff, Timothy L.

1990-01-01

An essential part of the efficient operation of any microbiology laboratory involved in sample analysis is a standard procedures manual. The purpose of this manual is to provide concise and well defined instructions on routine technical procedures involving sample analysis and methods for monitoring and maintaining quality control within the laboratory. Of equal importance is the safe operation of the laboratory. This manual outlines detailed procedures to be followed in the microbial ecology laboratory to assure safety, analytical control, and validity of results.

Pulmonary parenchyma segmentation in thin CT image sequences with spectral clustering and geodesic active contour model based on similarity

Science.gov (United States)

He, Nana; Zhang, Xiaolong; Zhao, Juanjuan; Zhao, Huilan; Qiang, Yan

2017-07-01

While the popular thin layer scanning technology of spiral CT has helped to improve diagnoses of lung diseases, the large volumes of scanning images produced by the technology also dramatically increase the load of physicians in lesion detection. Computer-aided diagnosis techniques like lesions segmentation in thin CT sequences have been developed to address this issue, but it remains a challenge to achieve high segmentation efficiency and accuracy without much involvement of human manual intervention. In this paper, we present our research on automated segmentation of lung parenchyma with an improved geodesic active contour model that is geodesic active contour model based on similarity (GACBS). Combining spectral clustering algorithm based on Nystrom (SCN) with GACBS, this algorithm first extracts key image slices, then uses these slices to generate an initial contour of pulmonary parenchyma of un-segmented slices with an interpolation algorithm, and finally segments lung parenchyma of un-segmented slices. Experimental results show that the segmentation results generated by our method are close to what manual segmentation can produce, with an average volume overlap ratio of 91.48%.

Fully automatic segmentation of left atrium and pulmonary veins in late gadolinium-enhanced MRI: Towards objective atrial scar assessment.

Science.gov (United States)

Tao, Qian; Ipek, Esra Gucuk; Shahzad, Rahil; Berendsen, Floris F; Nazarian, Saman; van der Geest, Rob J

2016-08-01

To realize objective atrial scar assessment, this study aimed to develop a fully automatic method to segment the left atrium (LA) and pulmonary veins (PV) from late gadolinium-enhanced (LGE) magnetic resonance imaging (MRI). The extent and distribution of atrial scar, visualized by LGE-MRI, provides important information for clinical treatment of atrial fibrillation (AF) patients. Forty-six AF patients (age 62 ± 8, 14 female) who underwent cardiac MRI prior to RF ablation were included. A contrast-enhanced MR angiography (MRA) sequence was acquired for anatomy assessment followed by an LGE sequence for LA scar assessment. A fully automatic segmentation method was proposed consisting of two stages: 1) global segmentation by multiatlas registration; and 2) local refinement by 3D level-set. These automatic segmentation results were compared with manual segmentation. The LA and PVs were automatically segmented in all subjects. Compared with manual segmentation, the method yielded a surface-to-surface distance of 1.49 ± 0.65 mm in the LA region when using both MRA and LGE, and 1.80 ± 0.93 mm when using LGE alone (P automatic and manual segmentation was comparable to the interobserver difference (P = 0.8 in LA region and P = 0.7 in PV region). We developed a fully automatic method for LA and PV segmentation from LGE-MRI, with comparable performance to a human observer. Inclusion of an MRA sequence further improves the segmentation accuracy. The method leads to automatic generation of a patient-specific model, and potentially enables objective atrial scar assessment for AF patients. J. Magn. Reson. Imaging 2016;44:346-354. © 2016 Wiley Periodicals, Inc.

Automated bone segmentation from large field of view 3D MR images of the hip joint

International Nuclear Information System (INIS)

Xia, Ying; Fripp, Jurgen; Chandra, Shekhar S; Schwarz, Raphael; Engstrom, Craig; Crozier, Stuart

2013-01-01

Accurate bone segmentation in the hip joint region from magnetic resonance (MR) images can provide quantitative data for examining pathoanatomical conditions such as femoroacetabular impingement through to varying stages of osteoarthritis to monitor bone and associated cartilage morphometry. We evaluate two state-of-the-art methods (multi-atlas and active shape model (ASM) approaches) on bilateral MR images for automatic 3D bone segmentation in the hip region (proximal femur and innominate bone). Bilateral MR images of the hip joints were acquired at 3T from 30 volunteers. Image sequences included water-excitation dual echo stead state (FOV 38.6 × 24.1 cm, matrix 576 × 360, thickness 0.61 mm) in all subjects and multi-echo data image combination (FOV 37.6 × 23.5 cm, matrix 576 × 360, thickness 0.70 mm) for a subset of eight subjects. Following manual segmentation of femoral (head–neck, proximal-shaft) and innominate (ilium+ischium+pubis) bone, automated bone segmentation proceeded via two approaches: (1) multi-atlas segmentation incorporating non-rigid registration and (2) an advanced ASM-based scheme. Mean inter- and intra-rater reliability Dice's similarity coefficients (DSC) for manual segmentation of femoral and innominate bone were (0.970, 0.963) and (0.971, 0.965). Compared with manual data, mean DSC values for femoral and innominate bone volumes using automated multi-atlas and ASM-based methods were (0.950, 0.922) and (0.946, 0.917), respectively. Both approaches delivered accurate (high DSC values) segmentation results; notably, ASM data were generated in substantially less computational time (12 min versus 10 h). Both automated algorithms provided accurate 3D bone volumetric descriptions for MR-based measures in the hip region. The highly computational efficient ASM-based approach is more likely suitable for future clinical applications such as extracting bone–cartilage interfaces for potential cartilage segmentation. (paper)

Automated bone segmentation from large field of view 3D MR images of the hip joint

Science.gov (United States)

Xia, Ying; Fripp, Jurgen; Chandra, Shekhar S.; Schwarz, Raphael; Engstrom, Craig; Crozier, Stuart

2013-10-01

Accurate bone segmentation in the hip joint region from magnetic resonance (MR) images can provide quantitative data for examining pathoanatomical conditions such as femoroacetabular impingement through to varying stages of osteoarthritis to monitor bone and associated cartilage morphometry. We evaluate two state-of-the-art methods (multi-atlas and active shape model (ASM) approaches) on bilateral MR images for automatic 3D bone segmentation in the hip region (proximal femur and innominate bone). Bilateral MR images of the hip joints were acquired at 3T from 30 volunteers. Image sequences included water-excitation dual echo stead state (FOV 38.6 × 24.1 cm, matrix 576 × 360, thickness 0.61 mm) in all subjects and multi-echo data image combination (FOV 37.6 × 23.5 cm, matrix 576 × 360, thickness 0.70 mm) for a subset of eight subjects. Following manual segmentation of femoral (head-neck, proximal-shaft) and innominate (ilium+ischium+pubis) bone, automated bone segmentation proceeded via two approaches: (1) multi-atlas segmentation incorporating non-rigid registration and (2) an advanced ASM-based scheme. Mean inter- and intra-rater reliability Dice's similarity coefficients (DSC) for manual segmentation of femoral and innominate bone were (0.970, 0.963) and (0.971, 0.965). Compared with manual data, mean DSC values for femoral and innominate bone volumes using automated multi-atlas and ASM-based methods were (0.950, 0.922) and (0.946, 0.917), respectively. Both approaches delivered accurate (high DSC values) segmentation results; notably, ASM data were generated in substantially less computational time (12 min versus 10 h). Both automated algorithms provided accurate 3D bone volumetric descriptions for MR-based measures in the hip region. The highly computational efficient ASM-based approach is more likely suitable for future clinical applications such as extracting bone-cartilage interfaces for potential cartilage segmentation.

Interactive lung segmentation in abnormal human and animal chest CT scans

International Nuclear Information System (INIS)

Kockelkorn, Thessa T. J. P.; Viergever, Max A.; Schaefer-Prokop, Cornelia M.; Bozovic, Gracijela; Muñoz-Barrutia, Arrate; Rikxoort, Eva M. van; Brown, Matthew S.; Jong, Pim A. de; Ginneken, Bram van

2014-01-01

Purpose: Many medical image analysis systems require segmentation of the structures of interest as a first step. For scans with gross pathology, automatic segmentation methods may fail. The authors’ aim is to develop a versatile, fast, and reliable interactive system to segment anatomical structures. In this study, this system was used for segmenting lungs in challenging thoracic computed tomography (CT) scans. Methods: In volumetric thoracic CT scans, the chest is segmented and divided into 3D volumes of interest (VOIs), containing voxels with similar densities. These VOIs are automatically labeled as either lung tissue or nonlung tissue. The automatic labeling results can be corrected using an interactive or a supervised interactive approach. When using the supervised interactive system, the user is shown the classification results per slice, whereupon he/she can adjust incorrect labels. The system is retrained continuously, taking the corrections and approvals of the user into account. In this way, the system learns to make a better distinction between lung tissue and nonlung tissue. When using the interactive framework without supervised learning, the user corrects all incorrectly labeled VOIs manually. Both interactive segmentation tools were tested on 32 volumetric CT scans of pigs, mice and humans, containing pulmonary abnormalities. Results: On average, supervised interactive lung segmentation took under 9 min of user interaction. Algorithm computing time was 2 min on average, but can easily be reduced. On average, 2.0% of all VOIs in a scan had to be relabeled. Lung segmentation using the interactive segmentation method took on average 13 min and involved relabeling 3.0% of all VOIs on average. The resulting segmentations correspond well to manual delineations of eight axial slices per scan, with an average Dice similarity coefficient of 0.933. Conclusions: The authors have developed two fast and reliable methods for interactive lung segmentation in

DOE explosives safety manual. Revision 7

Energy Technology Data Exchange (ETDEWEB)

1994-08-01

This manual prescribes the Department of Energy (DOE) safety rules used to implement the DOE safety policy for operations involving explosives. This manual is applicable to all DOE facilities engaged in operations of development, manufacturing, handling, storage, transportation, processing, or testing of explosives, pyrotechnics and propellants, or assemblies containing these materials. The standards of this manual deal with the operations involving explosives, pyrotechnics and propellants, and the safe management of such operations. The design of all new explosives facilities shall conform to the requirements established in this manual and implemented in DOE 6430.1A, ``General Design Criteria Manual.`` It is not intended that existing physical facilities be changed arbitrarily to comply with these provisions, except as required by law. Existing facilities that do not comply with these standards may continue to be used for the balance of their functional life, as long as the current operation presents no significantly greater risk than that assumed when the facility was originally designed and it can be demonstrated clearly that a modification to bring the facility into compliance is not feasible. However, in the case of a major renovation, the facility must be brought into compliance with current standards. The standards are presented as either mandatory or advisory. Mandatory standards, denoted by the words ``shall,`` ``must,`` or ``will,`` are requirements that must be followed unless written authority for deviation is granted as an exemption by the DOE. Advisory standards denoted by ``should`` or ``may`` are standards that may be deviated from with a waiver granted by facility management.

Automated and simultaneous fovea center localization and macula segmentation using the new dynamic identification and classification of edges model

Science.gov (United States)

Onal, Sinan; Chen, Xin; Satamraju, Veeresh; Balasooriya, Maduka; Dabil-Karacal, Humeyra

2016-01-01

Abstract. Detecting the position of retinal structures, including the fovea center and macula, in retinal images plays a key role in diagnosing eye diseases such as optic nerve hypoplasia, amblyopia, diabetic retinopathy, and macular edema. However, current detection methods are unreliable for infants or certain ethnic populations. Thus, a methodology is proposed here that may be useful for infants and across ethnicities that automatically localizes the fovea center and segments the macula on digital fundus images. First, dark structures and bright artifacts are removed from the input image using preprocessing operations, and the resulting image is transformed to polar space. Second, the fovea center is identified, and the macula region is segmented using the proposed dynamic identification and classification of edges (DICE) model. The performance of the method was evaluated using 1200 fundus images obtained from the relatively large, diverse, and publicly available Messidor database. In 96.1% of these 1200 cases, the distance between the fovea center identified manually by ophthalmologists and automatically using the proposed method remained within 0 to 8 pixels. The dice similarity index comparing the manually obtained results with those of the model for macula segmentation was 96.12% for these 1200 cases. Thus, the proposed method displayed a high degree of accuracy. The methodology using the DICE model is unique and advantageous over previously reported methods because it simultaneously determines the fovea center and segments the macula region without using any structural information, such as optic disc or blood vessel location, and it may prove useful for all populations, including infants. PMID:27660803

A prescribed wake rotor inflow and flow field prediction analysis, user's manual and technical approach

Science.gov (United States)

Egolf, T. A.; Landgrebe, A. J.

1982-01-01

A user's manual is provided which includes the technical approach for the Prescribed Wake Rotor Inflow and Flow Field Prediction Analysis. The analysis is used to provide the rotor wake induced velocities at the rotor blades for use in blade airloads and response analyses and to provide induced velocities at arbitrary field points such as at a tail surface. This analysis calculates the distribution of rotor wake induced velocities based on a prescribed wake model. Section operating conditions are prescribed from blade motion and controls determined by a separate blade response analysis. The analysis represents each blade by a segmented lifting line, and the rotor wake by discrete segmented trailing vortex filaments. Blade loading and circulation distributions are calculated based on blade element strip theory including the local induced velocity predicted by the numerical integration of the Biot-Savart Law applied to the vortex wake model.

Development and Implementation of a Corriedale Ovine Brain Atlas for Use in Atlas-Based Segmentation.

Directory of Open Access Journals (Sweden)

Kishan Andre Liyanage

Full Text Available Segmentation is the process of partitioning an image into subdivisions and can be applied to medical images to isolate anatomical or pathological areas for further analysis. This process can be done manually or automated by the use of image processing computer packages. Atlas-based segmentation automates this process by the use of a pre-labelled template and a registration algorithm. We developed an ovine brain atlas that can be used as a model for neurological conditions such as Parkinson's disease and focal epilepsy. 17 female Corriedale ovine brains were imaged in-vivo in a 1.5T (low-resolution MRI scanner. 13 of the low-resolution images were combined using a template construction algorithm to form a low-resolution template. The template was labelled to form an atlas and tested by comparing manual with atlas-based segmentations against the remaining four low-resolution images. The comparisons were in the form of similarity metrics used in previous segmentation research. Dice Similarity Coefficients were utilised to determine the degree of overlap between eight independent, manual and atlas-based segmentations, with values ranging from 0 (no overlap to 1 (complete overlap. For 7 of these 8 segmented areas, we achieved a Dice Similarity Coefficient of 0.5-0.8. The amygdala was difficult to segment due to its variable location and similar intensity to surrounding tissues resulting in Dice Coefficients of 0.0-0.2. We developed a low resolution ovine brain atlas with eight clinically relevant areas labelled. This brain atlas performed comparably to prior human atlases described in the literature and to intra-observer error providing an atlas that can be used to guide further research using ovine brains as a model and is hosted online for public access.

PFPF canister counter for foreign plutonium (PCAS-3) hardware operations and procedures manual

International Nuclear Information System (INIS)

Menlove, H.O.; Baca, J.; Kroncke, K.E.; Miller, M.C.; Takahashi, S.; Seki, S.; Inose, S.; Yamamoto, T.

1993-01-01

A neutron coincidence counter has been designed for the measurement of plutonium powder contained in tall storage canisters. The counter was designed for installation in the Plutonium Fuel Production Facility fabrication plant. Each canister contains from one to five cans of PuO 2 . The neutron counter measures the spontaneous-fission rate from the plutonium and, when this is combined with the plutonium isotopic ratios, the plutonium mass is determined. The system can accommodate plutonium loadings up to 12 kg, with 10 kg being a typical loading. Software has been developed to permit the continuous operation of the system in an unattended mode. Authentication techniques have been developed for the system. This manual describes the system and its operation and gives performance and calibration parameters for typical applications

Simulation model for wind energy storage systems. Volume II. Operation manual. [SIMWEST code

Energy Technology Data Exchange (ETDEWEB)

Warren, A.W.; Edsinger, R.W.; Burroughs, J.D.

1977-08-01

The effort developed a comprehensive computer program for the modeling of wind energy/storage systems utilizing any combination of five types of storage (pumped hydro, battery, thermal, flywheel and pneumatic). An acronym for the program is SIMWEST (Simulation Model for Wind Energy Storage). The level of detail of SIMWEST is consistent with a role of evaluating the economic feasibility as well as the general performance of wind energy systems. The software package consists of two basic programs and a library of system, environmental, and load components. Volume II, the SIMWEST operation manual, describes the usage of the SIMWEST program, the design of the library components, and a number of simple example simulations intended to familiarize the user with the program's operation. Volume II also contains a listing of each SIMWEST library subroutine.

A Course on Operational Considerations in Wastewater Treatment Plant Design. Instructor's Manual.

Science.gov (United States)

Cooper, John W.; And Others

This manual contains 17 instructional units (sequenced to correspond to parallel chapters in a student's manual) focusing on upgrading the design of wastewater plant facilities and serving as a reference source for establishing criteria for upgrading wastewater treatment plants. The manual also furnishes information for modifying plant design to…

Fuel Element Technical Manual

Energy Technology Data Exchange (ETDEWEB)

Burley, H.H. [ed.

1956-08-01

It is the purpose of the Fuel Element Technical Manual to Provide a single document describing the fabrication processes used in the manufacture of the fuel element as well as the technical bases for these processes. The manual will be instrumental in the indoctrination of personnel new to the field and will provide a single data reference for all personnel involved in the design or manufacture of the fuel element. The material contained in this manual was assembled by members of the Engineering Department and the Manufacturing Department at the Hanford Atomic Products Operation between the dates October, 1955 and June, 1956. Arrangement of the manual. The manual is divided into six parts: Part I--introduction; Part II--technical bases; Part III--process; Part IV--plant and equipment; Part V--process control and improvement; and VI--safety.

Ranked retrieval of segmented nuclei for objective assessment of cancer gene repositioning

Directory of Open Access Journals (Sweden)

Cukierski William J

2012-09-01

Full Text Available Abstract Background Correct segmentation is critical to many applications within automated microscopy image analysis. Despite the availability of advanced segmentation algorithms, variations in cell morphology, sample preparation, and acquisition settings often lead to segmentation errors. This manuscript introduces a ranked-retrieval approach using logistic regression to automate selection of accurately segmented nuclei from a set of candidate segmentations. The methodology is validated on an application of spatial gene repositioning in breast cancer cell nuclei. Gene repositioning is analyzed in patient tissue sections by labeling sequences with fluorescence in situ hybridization (FISH, followed by measurement of the relative position of each gene from the nuclear center to the nuclear periphery. This technique requires hundreds of well-segmented nuclei per sample to achieve statistical significance. Although the tissue samples in this study contain a surplus of available nuclei, automatic identification of the well-segmented subset remains a challenging task. Results Logistic regression was applied to features extracted from candidate segmented nuclei, including nuclear shape, texture, context, and gene copy number, in order to rank objects according to the likelihood of being an accurately segmented nucleus. The method was demonstrated on a tissue microarray dataset of 43 breast cancer patients, comprising approximately 40,000 imaged nuclei in which the HES5 and FRA2 genes were labeled with FISH probes. Three trained reviewers independently classified nuclei into three classes of segmentation accuracy. In man vs. machine studies, the automated method outperformed the inter-observer agreement between reviewers, as measured by area under the receiver operating characteristic (ROC curve. Robustness of gene position measurements to boundary inaccuracies was demonstrated by comparing 1086 manually and automatically segmented nuclei. Pearson

A hybrid segmentation approach for geographic atrophy in fundus auto-fluorescence images for diagnosis of age-related macular degeneration.

Science.gov (United States)

Lee, Noah; Laine, Andrew F; Smith, R Theodore

2007-01-01

Fundus auto-fluorescence (FAF) images with hypo-fluorescence indicate geographic atrophy (GA) of the retinal pigment epithelium (RPE) in age-related macular degeneration (AMD). Manual quantification of GA is time consuming and prone to inter- and intra-observer variability. Automatic quantification is important for determining disease progression and facilitating clinical diagnosis of AMD. In this paper we describe a hybrid segmentation method for GA quantification by identifying hypo-fluorescent GA regions from other interfering retinal vessel structures. First, we employ background illumination correction exploiting a non-linear adaptive smoothing operator. Then, we use the level set framework to perform segmentation of hypo-fluorescent areas. Finally, we present an energy function combining morphological scale-space analysis with a geometric model-based approach to perform segmentation refinement of false positive hypo- fluorescent areas due to interfering retinal structures. The clinically apparent areas of hypo-fluorescence were drawn by an expert grader and compared on a pixel by pixel basis to our segmentation results. The mean sensitivity and specificity of the ROC analysis were 0.89 and 0.98%.

Operation and management manual of JT-60 experimental data analysis system

International Nuclear Information System (INIS)

Hirayama, Takashi; Morishima, Soichi

2014-03-01

In the Japan Atomic Energy Agency Naka Fusion Institute, a lot of experiments have been conducted by using the large tokamak device JT-60 aiming to realize fusion power plant. In order to optimize the JT-60 experiment and to investigate complex characteristics of plasma, JT-60 experimental data analysis system was developed and used for collecting, referring and analyzing the JT-60 experimental data. Main components of the system are a data analysis server and a database server for the analyses and accumulation of the experimental data respectively. Other peripheral devices of the system are magnetic disk units, NAS (Network Attached Storage) device, and a backup tape drive. This is an operation and management manual the JT-60 experimental data analysis system. (author)

Stepping motor control processor reference manual. Volume I

International Nuclear Information System (INIS)

Holloway, F.W.; VanArsdall, P.J.; Suski, G.J.; Gant, R.G.; Rash, M.

1980-01-01

This manual is intended to serve several purposes. The first goal is to describe the capabilities and operation of the SMC processor package from an operator or user point of view. Secondly, the manual will describe in some detail the basic hardware elements and how they can be used effectively to implement a step motor control system. Practical information on the use, installation and checkout of the hardware set is presented in the following sections along with programming suggestions. Available related system software is described in this manual for reference and as an aid in understanding the system architecture. Section two presents an overview and operations manual of the SMC processor describing its composition and functional capabilities. Section three contains hardware descriptions in some detail for the LLL-designed hardware used in the SMC processor. Basic theory of operation and important features are explained

DOSAR/CalLab Operations Manual

International Nuclear Information System (INIS)

Bogard, J.S.

2000-01-01

The Life Sciences Division (LSD) of Oak Ridge National Laboratory (ORNL) has a long record of radiation dosimetry research, primarily using the Health Physics Research Reactor (HPRR) and the Dosimetry Applications Research (DOSAR) Program Calibration Laboratory (CalLab), referred to formerly as the Radiation Calibration Laboratory. These facilities have been used by a broad segment of the research community to perform a variety of experiments in areas including, but not limited to, radiobiology, radiation dosimeter and instrumentation development and calibration, and the testing of materials in a variety of radiation environments

Robust Machine Learning-Based Correction on Automatic Segmentation of the Cerebellum and Brainstem.

Science.gov (United States)

Wang, Jun Yi; Ngo, Michael M; Hessl, David; Hagerman, Randi J; Rivera, Susan M

2016-01-01

Automated segmentation is a useful method for studying large brain structures such as the cerebellum and brainstem. However, automated segmentation may lead to inaccuracy and/or undesirable boundary. The goal of the present study was to investigate whether SegAdapter, a machine learning-based method, is useful for automatically correcting large segmentation errors and disagreement in anatomical definition. We further assessed the robustness of the method in handling size of training set, differences in head coil usage, and amount of brain atrophy. High resolution T1-weighted images were acquired from 30 healthy controls scanned with either an 8-channel or 32-channel head coil. Ten patients, who suffered from brain atrophy because of fragile X-associated tremor/ataxia syndrome, were scanned using the 32-channel head coil. The initial segmentations of the cerebellum and brainstem were generated automatically using Freesurfer. Subsequently, Freesurfer's segmentations were both manually corrected to serve as the gold standard and automatically corrected by SegAdapter. Using only 5 scans in the training set, spatial overlap with manual segmentation in Dice coefficient improved significantly from 0.956 (for Freesurfer segmentation) to 0.978 (for SegAdapter-corrected segmentation) for the cerebellum and from 0.821 to 0.954 for the brainstem. Reducing the training set size to 2 scans only decreased the Dice coefficient ≤0.002 for the cerebellum and ≤ 0.005 for the brainstem compared to the use of training set size of 5 scans in corrective learning. The method was also robust in handling differences between the training set and the test set in head coil usage and the amount of brain atrophy, which reduced spatial overlap only by segmentation and corrective learning provides a valuable method for accurate and efficient segmentation of the cerebellum and brainstem, particularly in large-scale neuroimaging studies, and potentially for segmenting other neural regions as

Modeling vehicle interior noise exposure dose on freeways: Considering weaving segment designs and engine operation.

Science.gov (United States)

Li, Qing; Qiao, Fengxiang; Yu, Lei; Shi, Junqing

2017-07-05

Vehicle interior noise functions at the dominant frequencies of 500 Hz below and around 800 Hz, which fall into the bands that may impair hearing. Recent studies demonstrated that freeway commuters are chronically exposed to vehicle interior noise, bearing the risk of hearing impairment. The interior noise evaluation process is mostly conducted in a laboratory environment. The test results and the developed noise models may underestimate or ignore the noise effects from dynamic traffic and road conditions and configuration. However, the interior noise is highly associated with vehicle maneuvering. The vehicle maneuvering on a freeway weaving segment is more complex because of its nature of conflicting areas. This research is intended to explore the risk of the interior noise exposure on freeway weaving segments for freeway commuters and to improve the interior noise estimation by constructing a decision tree learning-based noise exposure dose (NED) model, considering weaving segment designs and engine operation. On-road driving tests were conducted on 12 subjects on State Highway 288 in Houston, Texas. On-board Diagnosis (OBD) II, a smartphone-based roughness app, and a digital sound meter were used to collect vehicle maneuvering and engine information, International Roughness Index, and interior noise levels, respectively. Eleven variables were obtainable from the driving tests, including the length and type of a weaving segment, serving as predictors. The importance of the predictors was estimated by their out-of-bag-permuted predictor delta errors. The hazardous exposure level of the interior noise on weaving segments was quantified to hazard quotient, NED, and daily noise exposure level, respectively. Results showed that the risk of hearing impairment on freeway is acceptable; the interior noise level is the most sensitive to the pavement roughness and is subject to freeway configuration and traffic conditions. The constructed NED model shows high predictive

Automatic segmentation of the lateral geniculate nucleus: Application to control and glaucoma patients.

Science.gov (United States)

Wang, Jieqiong; Miao, Wen; Li, Jing; Li, Meng; Zhen, Zonglei; Sabel, Bernhard; Xian, Junfang; He, Huiguang

2015-11-30

The lateral geniculate nucleus (LGN) is a key relay center of the visual system. Because the LGN morphology is affected by different diseases, it is of interest to analyze its morphology by segmentation. However, existing LGN segmentation methods are non-automatic, inefficient and prone to experimenters' bias. To address these problems, we proposed an automatic LGN segmentation algorithm based on T1-weighted imaging. First, the prior information of LGN was used to create a prior mask. Then region growing was applied to delineate LGN. We evaluated this automatic LGN segmentation method by (1) comparison with manually segmented LGN, (2) anatomically locating LGN in the visual system via LGN-based tractography, (3) application to control and glaucoma patients. The similarity coefficients of automatic segmented LGN and manually segmented one are 0.72 (0.06) for the left LGN and 0.77 (0.07) for the right LGN. LGN-based tractography shows the subcortical pathway seeding from LGN passes the optic tract and also reaches V1 through the optic radiation, which is consistent with the LGN location in the visual system. In addition, LGN asymmetry as well as LGN atrophy along with age is observed in normal controls. The investigation of glaucoma effects on LGN volumes demonstrates that the bilateral LGN volumes shrink in patients. The automatic LGN segmentation is objective, efficient, valid and applicable. Experiment results proved the validity and applicability of the algorithm. Our method will speed up the research on visual system and greatly enhance studies of different vision-related diseases. Copyright © 2015 Elsevier B.V. All rights reserved.

A study on traffic weaving segment level of service on Malaysia urban highway

Science.gov (United States)

Abdullah, Rohaya; Sadullah, Ahmad Farhan Mohd

2017-07-01

The objective of this research is to observe weaving problems, analyze the capacity of the weaving segment and to identify the behavior of the Malaysian driver at urban freeway weaving segment. Field data collected during non - peak hours at km. 138.6-138.2 (north bound) Seberang Jaya: Penang Bridge, km.16.8 to km.17.0 Sunway Mentari: Damansara-Puchong Highway and km.21.4 to km.21.9 Puchong Intan: Damansara-Puchong Highway. These segments behave as a bottleneck during peak hour. The data collected are traffic volume, vehicle composition and the road geometry. The drivers behavior pattern at the freeway weaving segment is observed. This research analyses by two different methodologies, the first analysis is by referring to the US Highway Capacity Manual 2010 and the second analysis through a modified method to suit the local traffic composition. The consideration of motorcycle and light heavy vehicle in the analysis lead to a different evaluation of weaving segment capacity. The analysis results show a slight difference between both methods. LOS, weaving speed and density prediction by the modified method is slightly higher than the HCM method. These results, suggest that the numbers of light heavy vehicle and motorcycle contribute to the amount of traffic volume because the value factors of Passenger Car Equivalent (PCE). The adoption of the widely used method without taking consideration of local traffic condition, might lead to improper road planning or design or road operation management.

Interactive prostate segmentation using atlas-guided semi-supervised learning and adaptive feature selection.

Science.gov (United States)

Park, Sang Hyun; Gao, Yaozong; Shi, Yinghuan; Shen, Dinggang

2014-11-01

Accurate prostate segmentation is necessary for maximizing the effectiveness of radiation therapy of prostate cancer. However, manual segmentation from 3D CT images is very time-consuming and often causes large intra- and interobserver variations across clinicians. Many segmentation methods have been proposed to automate this labor-intensive process, but tedious manual editing is still required due to the limited performance. In this paper, the authors propose a new interactive segmentation method that can (1) flexibly generate the editing result with a few scribbles or dots provided by a clinician, (2) fast deliver intermediate results to the clinician, and (3) sequentially correct the segmentations from any type of automatic or interactive segmentation methods. The authors formulate the editing problem as a semisupervised learning problem which can utilize a priori knowledge of training data and also the valuable information from user interactions. Specifically, from a region of interest near the given user interactions, the appropriate training labels, which are well matched with the user interactions, can be locally searched from a training set. With voting from the selected training labels, both confident prostate and background voxels, as well as unconfident voxels can be estimated. To reflect informative relationship between voxels, location-adaptive features are selected from the confident voxels by using regression forest and Fisher separation criterion. Then, the manifold configuration computed in the derived feature space is enforced into the semisupervised learning algorithm. The labels of unconfident voxels are then predicted by regularizing semisupervised learning algorithm. The proposed interactive segmentation method was applied to correct automatic segmentation results of 30 challenging CT images. The correction was conducted three times with different user interactions performed at different time periods, in order to evaluate both the efficiency

Study of automated segmentation of the cerebellum and brainstem on brain MR images

International Nuclear Information System (INIS)

Hayashi, Norio; Matsuura, Yukihiro; Sanada, Shigeru; Suzuki, Masayuki

2005-01-01

MR imaging is an important method for diagnosing abnormalities of the brain. This paper presents an automated method to segment the cerebellum and brainstem for brain MR images. MR images were obtained from 10 normal subjects (male 4, female 6; 22-75 years old, average 31.0 years) and 15 patients with brain atrophy (male 3, female 12; 62-85 years of age, average 76.0 years). The automated method consisted of the following four steps: segmentation of the brain on original images, detection of an upper plane of the cerebellum using the Hough transform, correction of the plane using three-dimensional (3D) information, and segmentation of the cerebellum and brainstem using the plane. The results indicated that the regions obtained by the automated method were visually similar to those obtained by a manual method. The average rates of coincidence between the automated method and manual method were 83.0±9.0% in normal subjects and 86.4±3.6% in patients. (author)

Manual lymphatic drainage and therapeutic ultrasound in liposuction and lipoabdominoplasty post-operative period

Directory of Open Access Journals (Sweden)

Igor F. B. Masson

2014-01-01

Full Text Available Background: Physiotherapy in the plastic surgery post-operative (PO is essential to provide means for an adequate and fast recovery as it restores function through the use of physiotherapeutic procedures. Aim: The aim of the following study is to verify the effects of the association between the manual lymphatic drainage and the therapeutic ultrasound on pain, oedema and the tissue fibrosis in liposuction and lipoabdominoplasty PO. Design: This is a clinical trial prospective. Materials and Methods: Eighteen women aged between 18 and 60 years participated in this study, in the late PO period following lipoabdominoplasty or liposuction in the abdomen, flanks and lower trunk, which showed tissue fibrosis of the flanks and abdomen regions. They were divided into two groups: Liposuction group and lipoabdominoplasty group. A total of twelve sessions of therapeutic ultrasound followed by the manual lymphatic drainage were performed. The patients were assessed with regard to pain, oedema and tissue fibrosis in different moments: Initial assessment, during assessment and final assessment through the application of the protocol of evaluation of cysts fibrosis levels. Statistical Analysis: The test of equality for two proportions and the confidence interval test for mean to evaluate the distribution of variables. The significance level adopted for statistical tests was 5% (P < 0.05. Results: There was a statistically significant reduction of pain, swelling and tissue fibrosis in both groups. Conclusion: the association between manual lymphatic drainage and the therapeutic ultrasound reduced the swelling and the tissue fibrosis and made pain disappear in liposuction and lipoabdominoplasty PO period.

Automatic ultrasound image enhancement for 2D semi-automatic breast-lesion segmentation

Science.gov (United States)

Lu, Kongkuo; Hall, Christopher S.

2014-03-01

Breast cancer is the fastest growing cancer, accounting for 29%, of new cases in 2012, and second leading cause of cancer death among women in the United States and worldwide. Ultrasound (US) has been used as an indispensable tool for breast cancer detection/diagnosis and treatment. In computer-aided assistance, lesion segmentation is a preliminary but vital step, but the task is quite challenging in US images, due to imaging artifacts that complicate detection and measurement of the suspect lesions. The lesions usually present with poor boundary features and vary significantly in size, shape, and intensity distribution between cases. Automatic methods are highly application dependent while manual tracing methods are extremely time consuming and have a great deal of intra- and inter- observer variability. Semi-automatic approaches are designed to counterbalance the advantage and drawbacks of the automatic and manual methods. However, considerable user interaction might be necessary to ensure reasonable segmentation for a wide range of lesions. This work proposes an automatic enhancement approach to improve the boundary searching ability of the live wire method to reduce necessary user interaction while keeping the segmentation performance. Based on the results of segmentation of 50 2D breast lesions in US images, less user interaction is required to achieve desired accuracy, i.e. < 80%, when auto-enhancement is applied for live-wire segmentation.

PSNet: prostate segmentation on MRI based on a convolutional neural network.

Science.gov (United States)

Tian, Zhiqiang; Liu, Lizhi; Zhang, Zhenfeng; Fei, Baowei

2018-04-01

Automatic segmentation of the prostate on magnetic resonance images (MRI) has many applications in prostate cancer diagnosis and therapy. We proposed a deep fully convolutional neural network (CNN) to segment the prostate automatically. Our deep CNN model is trained end-to-end in a single learning stage, which uses prostate MRI and the corresponding ground truths as inputs. The learned CNN model can be used to make an inference for pixel-wise segmentation. Experiments were performed on three data sets, which contain prostate MRI of 140 patients. The proposed CNN model of prostate segmentation (PSNet) obtained a mean Dice similarity coefficient of [Formula: see text] as compared to the manually labeled ground truth. Experimental results show that the proposed model could yield satisfactory segmentation of the prostate on MRI.

14 CFR 125.75 - Airplane flight manual.

Science.gov (United States)

2010-01-01

... 14 Aeronautics and Space 3 2010-01-01 2010-01-01 false Airplane flight manual. 125.75 Section 125... OPERATIONS: AIRPLANES HAVING A SEATING CAPACITY OF 20 OR MORE PASSENGERS OR A MAXIMUM PAYLOAD CAPACITY OF 6... Airplane flight manual. (a) Each certificate holder shall keep a current approved Airplane Flight Manual or...

Environment, safety, and health manual, closeout report

International Nuclear Information System (INIS)

1975-12-01

A coordination draft of the Environment, Safety, and Health (ES and H) manual was submitted on 2 September 1975. Comments provided by Operational Safety personnel were being incorporated by a task team when the effort was terminated on 31 October 1975. This report documents the development history of the manual and provides a status of the manual up to the time the efforts were discontinued. Also discussed are issues which effect completion of the manual. Additionally a plan for completion of the manual is suggested

Appearance Constrained Semi-Automatic Segmentation from DCE-MRI is Reproducible and Feasible for Breast Cancer Radiomics: A Feasibility Study.

Science.gov (United States)

Veeraraghavan, Harini; Dashevsky, Brittany Z; Onishi, Natsuko; Sadinski, Meredith; Morris, Elizabeth; Deasy, Joseph O; Sutton, Elizabeth J

2018-03-19

We present a segmentation approach that combines GrowCut (GC) with cancer-specific multi-parametric Gaussian Mixture Model (GCGMM) to produce accurate and reproducible segmentations. We evaluated GCGMM using a retrospectively collected 75 invasive ductal carcinoma with ERPR+ HER2- (n = 15), triple negative (TN) (n = 9), and ER-HER2+ (n = 57) cancers with variable presentation (mass and non-mass enhancement) and background parenchymal enhancement (mild and marked). Expert delineated manual contours were used to assess the segmentation performance using Dice coefficient (DSC), mean surface distance (mSD), Hausdorff distance, and volume ratio (VR). GCGMM segmentations were significantly more accurate than GrowCut (GC) and fuzzy c-means clustering (FCM). GCGMM's segmentations and the texture features computed from those segmentations were the most reproducible compared with manual delineations and other analyzed segmentation methods. Finally, random forest (RF) classifier trained with leave-one-out cross-validation using features extracted from GCGMM segmentation resulted in the best accuracy for ER-HER2+ vs. ERPR+/TN (GCGMM 0.95, expert 0.95, GC 0.90, FCM 0.92) and for ERPR + HER2- vs. TN (GCGMM 0.92, expert 0.91, GC 0.77, FCM 0.83).

Standard Hydrogen Monitoring System-C operation and maintenance manual

International Nuclear Information System (INIS)

Schneider, T.C.

1997-01-01

The primary function of the SHMS-C is to monitor specifically for hydrogen in the waste tank vapor space which may also contain (but not be limited to) unknown quantities of air, nitrous oxide (N 2 O), ammonia (NH 3 ), water vapor, carbon dioxide (CO 2 ), carbon monoxide (CO) and other gaseous constituents. An electronically controlled grab sampler has replaced the manually operated sample system that was used in the original SHMS enclosure. Samples can now be operator or automatically initiated. Automatic initiation occurs based on the high hydrogen alarm level. Once a sample is obtained it is removed from the sampler and transported to a laboratory for analysis. This system is used to identify other gaseous constituents which are not measured by the hydrogen monitor. The design does not include any remote data acquisition or remote data logging equipment but provides a 4--20 mA dc process signals, and discrete alarm contacts, that can be utilized for remote data logging and alarming when desired. The SHMS-C arrangement consists of design modifications (piping, valves, filters, supports) to the SHMS-B arrangement necessary for the installation of a dual column gas chromatograph and associated sample and calibration gas lines. The gas chromatograph will provide real time, analytical quality, specific hydrogen measurements in low and medium range concentrations. The system is designed to sample process gases that are classified by NEC code as Class 1, Division 1, Group B

Automatic lung segmentation in functional SPECT images using active shape models trained on reference lung shapes from CT.

Science.gov (United States)

Cheimariotis, Grigorios-Aris; Al-Mashat, Mariam; Haris, Kostas; Aletras, Anthony H; Jögi, Jonas; Bajc, Marika; Maglaveras, Nicolaos; Heiberg, Einar

2018-02-01

Image segmentation is an essential step in quantifying the extent of reduced or absent lung function. The aim of this study is to develop and validate a new tool for automatic segmentation of lungs in ventilation and perfusion SPECT images and compare automatic and manual SPECT lung segmentations with reference computed tomography (CT) volumes. A total of 77 subjects (69 patients with obstructive lung disease, and 8 subjects without apparent perfusion of ventilation loss) performed low-dose CT followed by ventilation/perfusion (V/P) SPECT examination in a hybrid gamma camera system. In the training phase, lung shapes from the 57 anatomical low-dose CT images were used to construct two active shape models (right lung and left lung) which were then used for image segmentation. The algorithm was validated in 20 patients, comparing its results to reference delineation of corresponding CT images, and by comparing automatic segmentation to manual delineations in SPECT images. The Dice coefficient between automatic SPECT delineations and manual SPECT delineations were 0.83 ± 0.04% for the right and 0.82 ± 0.05% for the left lung. There was statistically significant difference between reference volumes from CT and automatic delineations for the right (R = 0.53, p = 0.02) and left lung (R = 0.69, p automatic quantification of wide range of measurements.

Bayesian automated cortical segmentation for neonatal MRI

Science.gov (United States)

Chou, Zane; Paquette, Natacha; Ganesh, Bhavana; Wang, Yalin; Ceschin, Rafael; Nelson, Marvin D.; Macyszyn, Luke; Gaonkar, Bilwaj; Panigrahy, Ashok; Lepore, Natasha

2017-11-01

Several attempts have been made in the past few years to develop and implement an automated segmentation of neonatal brain structural MRI. However, accurate automated MRI segmentation remains challenging in this population because of the low signal-to-noise ratio, large partial volume effects and inter-individual anatomical variability of the neonatal brain. In this paper, we propose a learning method for segmenting the whole brain cortical grey matter on neonatal T2-weighted images. We trained our algorithm using a neonatal dataset composed of 3 fullterm and 4 preterm infants scanned at term equivalent age. Our segmentation pipeline combines the FAST algorithm from the FSL library software and a Bayesian segmentation approach to create a threshold matrix that minimizes the error of mislabeling brain tissue types. Our method shows promising results with our pilot training set. In both preterm and full-term neonates, automated Bayesian segmentation generates a smoother and more consistent parcellation compared to FAST, while successfully removing the subcortical structure and cleaning the edges of the cortical grey matter. This method show promising refinement of the FAST segmentation by considerably reducing manual input and editing required from the user, and further improving reliability and processing time of neonatal MR images. Further improvement will include a larger dataset of training images acquired from different manufacturers.

Semiautomated segmentation of head and neck cancers in 18F-FDG PET scans: A just-enough-interaction approach.

Science.gov (United States)

Beichel, Reinhard R; Van Tol, Markus; Ulrich, Ethan J; Bauer, Christian; Chang, Tangel; Plichta, Kristin A; Smith, Brian J; Sunderland, John J; Graham, Michael M; Sonka, Milan; Buatti, John M

2016-06-01

The purpose of this work was to develop, validate, and compare a highly computer-aided method for the segmentation of hot lesions in head and neck 18F-FDG PET scans. A semiautomated segmentation method was developed, which transforms the segmentation problem into a graph-based optimization problem. For this purpose, a graph structure around a user-provided approximate lesion centerpoint is constructed and a suitable cost function is derived based on local image statistics. To handle frequently occurring situations that are ambiguous (e.g., lesions adjacent to each other versus lesion with inhomogeneous uptake), several segmentation modes are introduced that adapt the behavior of the base algorithm accordingly. In addition, the authors present approaches for the efficient interactive local and global refinement of initial segmentations that are based on the "just-enough-interaction" principle. For method validation, 60 PET/CT scans from 59 different subjects with 230 head and neck lesions were utilized. All patients had squamous cell carcinoma of the head and neck. A detailed comparison with the current clinically relevant standard manual segmentation approach was performed based on 2760 segmentations produced by three experts. Segmentation accuracy measured by the Dice coefficient of the proposed semiautomated and standard manual segmentation approach was 0.766 and 0.764, respectively. This difference was not statistically significant (p = 0.2145). However, the intra- and interoperator standard deviations were significantly lower for the semiautomated method. In addition, the proposed method was found to be significantly faster and resulted in significantly higher intra- and interoperator segmentation agreement when compared to the manual segmentation approach. Lack of consistency in tumor definition is a critical barrier for radiation treatment targeting as well as for response assessment in clinical trials and in clinical oncology decision-making. The properties

Semiautomated segmentation of head and neck cancers in 18F-FDG PET scans: A just-enough-interaction approach

Energy Technology Data Exchange (ETDEWEB)

Beichel, Reinhard R., E-mail: reinhard-beichel@uiowa.edu [Department of Electrical and Computer Engineering, University of Iowa, Iowa City, Iowa 52242 (United States); Iowa Institute for Biomedical Imaging, University of Iowa, Iowa City, Iowa 52242 (United States); Department of Internal Medicine, University of Iowa, Iowa City, Iowa 52242 (United States); Van Tol, Markus; Ulrich, Ethan J.; Bauer, Christian [Department of Electrical and Computer Engineering, University of Iowa, Iowa City, Iowa 52242 (United States); Iowa Institute for Biomedical Imaging, The University of Iowa, Iowa City, Iowa 52242 (United States); Chang, Tangel; Plichta, Kristin A. [Department of Radiation Oncology, University of Iowa, Iowa City, Iowa 52242 (United States); Smith, Brian J. [Department of Biostatistics, University of Iowa, Iowa City, Iowa 52242 (United States); Sunderland, John J.; Graham, Michael M. [Department of Radiology, University of Iowa, Iowa City, Iowa 52242 (United States); Sonka, Milan [Department of Electrical and Computer Engineering, University of Iowa, Iowa City, Iowa 52242 (United States); Department of Radiation Oncology, The University of Iowa, Iowa City, Iowa 52242 (United States); Iowa Institute for Biomedical Imaging, University of Iowa, Iowa City, Iowa 52242 (United States); Buatti, John M. [Department of Radiation Oncology, University of Iowa, Iowa City, Iowa 52242 (United States); Iowa Institute for Biomedical Imaging, University of Iowa, Iowa City, Iowa 52242 (United States)

2016-06-15

Purpose: The purpose of this work was to develop, validate, and compare a highly computer-aided method for the segmentation of hot lesions in head and neck 18F-FDG PET scans. Methods: A semiautomated segmentation method was developed, which transforms the segmentation problem into a graph-based optimization problem. For this purpose, a graph structure around a user-provided approximate lesion centerpoint is constructed and a suitable cost function is derived based on local image statistics. To handle frequently occurring situations that are ambiguous (e.g., lesions adjacent to each other versus lesion with inhomogeneous uptake), several segmentation modes are introduced that adapt the behavior of the base algorithm accordingly. In addition, the authors present approaches for the efficient interactive local and global refinement of initial segmentations that are based on the “just-enough-interaction” principle. For method validation, 60 PET/CT scans from 59 different subjects with 230 head and neck lesions were utilized. All patients had squamous cell carcinoma of the head and neck. A detailed comparison with the current clinically relevant standard manual segmentation approach was performed based on 2760 segmentations produced by three experts. Results: Segmentation accuracy measured by the Dice coefficient of the proposed semiautomated and standard manual segmentation approach was 0.766 and 0.764, respectively. This difference was not statistically significant (p = 0.2145). However, the intra- and interoperator standard deviations were significantly lower for the semiautomated method. In addition, the proposed method was found to be significantly faster and resulted in significantly higher intra- and interoperator segmentation agreement when compared to the manual segmentation approach. Conclusions: Lack of consistency in tumor definition is a critical barrier for radiation treatment targeting as well as for response assessment in clinical trials and in

A direct morphometric comparison of five labeling protocols for multi-atlas driven automatic segmentation of the hippocampus in Alzheimer's disease.

Science.gov (United States)

Nestor, Sean M; Gibson, Erin; Gao, Fu-Qiang; Kiss, Alex; Black, Sandra E

2013-02-01

Hippocampal volumetry derived from structural MRI is increasingly used to delineate regions of interest for functional measurements, assess efficacy in therapeutic trials of Alzheimer's disease (AD) and has been endorsed by the new AD diagnostic guidelines as a radiological marker of disease progression. Unfortunately, morphological heterogeneity in AD can prevent accurate demarcation of the hippocampus. Recent developments in automated volumetry commonly use multi-template fusion driven by expert manual labels, enabling highly accurate and reproducible segmentation in disease and healthy subjects. However, there are several protocols to define the hippocampus anatomically in vivo, and the method used to generate atlases may impact automatic accuracy and sensitivity - particularly in pathologically heterogeneous samples. Here we report a fully automated segmentation technique that provides a robust platform to directly evaluate both technical and biomarker performance in AD among anatomically unique labeling protocols. For the first time we test head-to-head the performance of five common hippocampal labeling protocols for multi-atlas based segmentation, using both the Sunnybrook Longitudinal Dementia Study and the entire Alzheimer's Disease Neuroimaging Initiative 1 (ADNI-1) baseline and 24-month dataset. We based these atlas libraries on the protocols of (Haller et al., 1997; Killiany et al., 1993; Malykhin et al., 2007; Pantel et al., 2000; Pruessner et al., 2000), and a single operator performed all manual tracings to generate de facto "ground truth" labels. All methods distinguished between normal elders, mild cognitive impairment (MCI), and AD in the expected directions, and showed comparable correlations with measures of episodic memory performance. Only more inclusive protocols distinguished between stable MCI and MCI-to-AD converters, and had slightly better associations with episodic memory. Moreover, we demonstrate that protocols including more posterior

Operations and Maintenance Manual for Full-Scale Bioventing System at FSA-1, Air Force Plant 4, Fort Worth, Texas

National Research Council Canada - National Science Library

1996-01-01

This Operations and Maintenance (O&M) Manual has been created as a guide for monitoring and maintaining the performance of the full-scale bioventing blower system and vent well plumbing at FSA-1 at Air Force Plant 4 (AFP4), Texas...

Resource Conservation and Recovery Act (RCRA) new-employee training manual for the Operations Division RCRA personnel

Energy Technology Data Exchange (ETDEWEB)

Barkenbus, B.D.

1987-03-01

This manual has been prepared for the training of new employees who will work with RCRA hazardous waste management in the Operations Division. It will be taught by a person who is trained in hazardous waste regulations/procedures. It consists of nine modules. The topics of these modules are: RCRA Training, Hazardous Waste Regulations, Transportation Regulations, Hazardous Waste Management at ORNL, Chemical Hazards and Safety, Hazardous Waste Operations Training, Sampling of Hazardous Waste, Hazardous Waste Identification/Classification, and RCRA Contingency Plans and Emergency Procedures. The on-the-job training areas are identified in the modules. They are an integral part of training.

21 CFR 892.5650 - Manual radionuclide applicator system.

Science.gov (United States)

2010-04-01

... system. (a) Identification. A manual radionuclide applicator system is a manually operated device... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Manual radionuclide applicator system. 892.5650.... This generic type of device may include patient and equipment supports, component parts, treatment...

Segmentation of a Vibro-Shock Cantilever-Type Piezoelectric Energy Harvester Operating in Higher Transverse Vibration Modes

Directory of Open Access Journals (Sweden)

Darius Zizys

2015-12-01

Full Text Available The piezoelectric transduction mechanism is a common vibration-to-electric energy harvesting approach. Piezoelectric energy harvesters are typically mounted on a vibrating host structure, whereby alternating voltage output is generated by a dynamic strain field. A design target in this case is to match the natural frequency of the harvester to the ambient excitation frequency for the device to operate in resonance mode, thus significantly increasing vibration amplitudes and, as a result, energy output. Other fundamental vibration modes have strain nodes, where the dynamic strain field changes sign in the direction of the cantilever length. The paper reports on a dimensionless numerical transient analysis of a cantilever of a constant cross-section and an optimally-shaped cantilever with the objective to accurately predict the position of a strain node. Total effective strain produced by both cantilevers segmented at the strain node is calculated via transient analysis and compared to the strain output produced by the cantilevers segmented at strain nodes obtained from modal analysis, demonstrating a 7% increase in energy output. Theoretical results were experimentally verified by using open-circuit voltage values measured for the cantilevers segmented at optimal and suboptimal segmentation lines.

Segment convolutional neural networks (Seg-CNNs) for classifying relations in clinical notes.

Science.gov (United States)

Luo, Yuan; Cheng, Yu; Uzuner, Özlem; Szolovits, Peter; Starren, Justin

2018-01-01

We propose Segment Convolutional Neural Networks (Seg-CNNs) for classifying relations from clinical notes. Seg-CNNs use only word-embedding features without manual feature engineering. Unlike typical CNN models, relations between 2 concepts are identified by simultaneously learning separate representations for text segments in a sentence: preceding, concept1, middle, concept2, and succeeding. We evaluate Seg-CNN on the i2b2/VA relation classification challenge dataset. We show that Seg-CNN achieves a state-of-the-art micro-average F-measure of 0.742 for overall evaluation, 0.686 for classifying medical problem-treatment relations, 0.820 for medical problem-test relations, and 0.702 for medical problem-medical problem relations. We demonstrate the benefits of learning segment-level representations. We show that medical domain word embeddings help improve relation classification. Seg-CNNs can be trained quickly for the i2b2/VA dataset on a graphics processing unit (GPU) platform. These results support the use of CNNs computed over segments of text for classifying medical relations, as they show state-of-the-art performance while requiring no manual feature engineering. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Consistent interactive segmentation of pulmonary ground glass nodules identified in CT studies

Science.gov (United States)

Zhang, Li; Fang, Ming; Naidich, David P.; Novak, Carol L.

2004-05-01

Ground glass nodules (GGNs) have proved especially problematic in lung cancer diagnosis, as despite frequently being malignant they characteristically have extremely slow rates of growth. This problem is further magnified by the small size of many of these lesions now being routinely detected following the introduction of multislice CT scanners capable of acquiring contiguous high resolution 1 to 1.25 mm sections throughout the thorax in a single breathhold period. Although segmentation of solid nodules can be used clinically to determine volume doubling times quantitatively, reliable methods for segmentation of pure ground glass nodules have yet to be introduced. Our purpose is to evaluate a newly developed computer-based segmentation method for rapid and reproducible measurements of pure ground glass nodules. 23 pure or mixed ground glass nodules were identified in a total of 8 patients by a radiologist and subsequently segmented by our computer-based method using Markov random field and shape analysis. The computer-based segmentation was initialized by a click point. Methodological consistency was assessed using the overlap ratio between 3 segmentations initialized by 3 different click points for each nodule. The 95% confidence interval on the mean of the overlap ratios proved to be [0.984, 0.998]. The computer-based method failed on two nodules that were difficult to segment even manually either due to especially low contrast or markedly irregular margins. While achieving consistent manual segmentation of ground glass nodules has proven problematic most often due to indistinct boundaries and interobserver variability, our proposed method introduces a powerful new tool for obtaining reproducible quantitative measurements of these lesions. It is our intention to further document the value of this approach with a still larger set of ground glass nodules.

Loosely coupled level sets for retinal layers and drusen segmentation in subjects with dry age-related macular degeneration

Science.gov (United States)

Novosel, Jelena; Wang, Ziyuan; de Jong, Henk; Vermeer, Koenraad A.; van Vliet, Lucas J.

2016-03-01

Optical coherence tomography (OCT) is used to produce high-resolution three-dimensional images of the retina, which permit the investigation of retinal irregularities. In dry age-related macular degeneration (AMD), a chronic eye disease that causes central vision loss, disruptions such as drusen and changes in retinal layer thicknesses occur which could be used as biomarkers for disease monitoring and diagnosis. Due to the topology disrupting pathology, existing segmentation methods often fail. Here, we present a solution for the segmentation of retinal layers in dry AMD subjects by extending our previously presented loosely coupled level sets framework which operates on attenuation coefficients. In eyes affected by AMD, Bruch's membrane becomes visible only below the drusen and our segmentation framework is adapted to delineate such a partially discernible interface. Furthermore, the initialization stage, which tentatively segments five interfaces, is modified to accommodate the appearance of drusen. This stage is based on Dijkstra's algorithm and combines prior knowledge on the shape of the interface, gradient and attenuation coefficient in the newly proposed cost function. This prior knowledge is incorporated by varying the weights for horizontal, diagonal and vertical edges. Finally, quantitative evaluation of the accuracy shows a good agreement between manual and automated segmentation.

Automated intraretinal layer segmentation of optical coherence tomography images using graph-theoretical methods

Science.gov (United States)

Roy, Priyanka; Gholami, Peyman; Kuppuswamy Parthasarathy, Mohana; Zelek, John; Lakshminarayanan, Vasudevan

2018-02-01

Segmentation of spectral-domain Optical Coherence Tomography (SD-OCT) images facilitates visualization and quantification of sub-retinal layers for diagnosis of retinal pathologies. However, manual segmentation is subjective, expertise dependent, and time-consuming, which limits applicability of SD-OCT. Efforts are therefore being made to implement active-contours, artificial intelligence, and graph-search to automatically segment retinal layers with accuracy comparable to that of manual segmentation, to ease clinical decision-making. Although, low optical contrast, heavy speckle noise, and pathologies pose challenges to automated segmentation. Graph-based image segmentation approach stands out from the rest because of its ability to minimize the cost function while maximising the flow. This study has developed and implemented a shortest-path based graph-search algorithm for automated intraretinal layer segmentation of SD-OCT images. The algorithm estimates the minimal-weight path between two graph-nodes based on their gradients. Boundary position indices (BPI) are computed from the transition between pixel intensities. The mean difference between BPIs of two consecutive layers quantify individual layer thicknesses, which shows statistically insignificant differences when compared to a previous study [for overall retina: p = 0.17, for individual layers: p > 0.05 (except one layer: p = 0.04)]. These results substantiate the accurate delineation of seven intraretinal boundaries in SD-OCT images by this algorithm, with a mean computation time of 0.93 seconds (64-bit Windows10, core i5, 8GB RAM). Besides being self-reliant for denoising, the algorithm is further computationally optimized to restrict segmentation within the user defined region-of-interest. The efficiency and reliability of this algorithm, even in noisy image conditions, makes it clinically applicable.

Segmentation of tumors in magnetic resonance brain images using an interactive multiscale watershed algorithm

DEFF Research Database (Denmark)

Letteboer, Marloes M J; Olsen, Ole F; Dam, Erik B

2004-01-01

RATIONALE AND OBJECTIVE: This article presents the evaluation of an interactive multiscale watershed segmentation algorithm for segmenting tumors in magnetic resonance brain images of patients scheduled for neuronavigational procedures. MATERIALS AND METHODS: The watershed method is compared...... delineation shows that the two methods are interchangeable according to the Bland and Altman criterion, and thus equally accurate. The repeatability of the watershed method and the manual method are compared by looking at the similarity of the segmented volumes. The similarity for intraobserver...

Lung Tumor Segmentation Using Electric Flow Lines for Graph Cuts

DEFF Research Database (Denmark)

Hollensen, Christian; Cannon, George; Cannon, Donald

2012-01-01

are normally only used for correction of movements. The method uses graphs based on electric flow lines. The method offers several advantages when trying to replicate manual segmentations. The method gave a dice coefficient of 0.85 and performed better than level set methods and deformable registration....

Facilitating coronary artery evaluation in MDCT using a 3D automatic vessel segmentation tool

International Nuclear Information System (INIS)

Fawad Khan, M.; Gurung, Jessen; Maataoui, Adel; Brehmer, Boris; Herzog, Christopher; Vogl, Thomas J.; Wesarg, Stefan; Dogan, Selami; Ackermann, Hanns; Assmus, Birgit

2006-01-01

The purpose of this study was to investigate a 3D coronary artery segmentation algorithm using 16-row MDCT data sets. Fifty patients underwent cardiac CT (Sensation 16, Siemens) and coronary angiography. Automatic and manual detection of coronary artery stenosis was performed. A 3D coronary artery segmentation algorithm (Fraunhofer Institute for Computer Graphics, Darmstadt) was used for automatic evaluation. All significant stenoses (>50%) in vessels >1.5 mm in diameter were protocoled. Each detection tool was used by one reader who was blinded to the results of the other detection method and the results of coronary angiography. Sensitivity and specificity were determined for automatic and manual detection as well as was the time for both CT-based evaluation methods. The overall sensitivity and specificity of the automatic and manual approach were 93.1 vs. 95.83% and 86.1 vs. 81.9%. The time required for automatic evaluation was significantly shorter than with the manual approach, i.e., 246.04±43.17 s for the automatic approach and 526.88±45.71 s for the manual approach (P<0.0001). In 94% of the coronary artery branches, automatic detection required less time than the manual approach. Automatic coronary vessel evaluation is feasible. It reduces the time required for cardiac CT evaluation with similar sensitivity and specificity as well as facilitates the evaluation of MDCT coronary angiography in a standardized fashion. (orig.)

Segmentation of multiple heart cavities in 3-D transesophageal ultrasound images.

Science.gov (United States)

Haak, Alexander; Vegas-Sánchez-Ferrero, Gonzalo; Mulder, Harriët W; Ren, Ben; Kirişli, Hortense A; Metz, Coert; van Burken, Gerard; van Stralen, Marijn; Pluim, Josien P W; van der Steen, Antonius F W; van Walsum, Theo; Bosch, Johannes G

2015-06-01

Three-dimensional transesophageal echocardiography (TEE) is an excellent modality for real-time visualization of the heart and monitoring of interventions. To improve the usability of 3-D TEE for intervention monitoring and catheter guidance, automated segmentation is desired. However, 3-D TEE segmentation is still a challenging task due to the complex anatomy with multiple cavities, the limited TEE field of view, and typical ultrasound artifacts. We propose to segment all cavities within the TEE view with a multi-cavity active shape model (ASM) in conjunction with a tissue/blood classification based on a gamma mixture model (GMM). 3-D TEE image data of twenty patients were acquired with a Philips X7-2t matrix TEE probe. Tissue probability maps were estimated by a two-class (blood/tissue) GMM. A statistical shape model containing the left ventricle, right ventricle, left atrium, right atrium, and aorta was derived from computed tomography angiography (CTA) segmentations by principal component analysis. ASMs of the whole heart and individual cavities were generated and consecutively fitted to tissue probability maps. First, an average whole-heart model was aligned with the 3-D TEE based on three manually indicated anatomical landmarks. Second, pose and shape of the whole-heart ASM were fitted by a weighted update scheme excluding parts outside of the image sector. Third, pose and shape of ASM for individual heart cavities were initialized by the previous whole heart ASM and updated in a regularized manner to fit the tissue probability maps. The ASM segmentations were validated against manual outlines by two observers and CTA derived segmentations. Dice coefficients and point-to-surface distances were used to determine segmentation accuracy. ASM segmentations were successful in 19 of 20 cases. The median Dice coefficient for all successful segmentations versus the average observer ranged from 90% to 71% compared with an inter-observer range of 95% to 84%. The

Manually-Operated Crate Dismantlement System for Los Alamos National Laboratory

International Nuclear Information System (INIS)

Laffitte, John; Lagos, Leo; Morales, Miguel

2002-01-01

Los Alamos National Laboratory currently possesses between 500 and 800 fiberglass-reinforced plywood crates that contain hazardous materials that need to be decontaminated. To access the hazardous material, a system is needed to dismantle the crate. Currently, crates are dismantled by workers using hand-held tools. This technique has numerous disadvantages. One disadvantage is that it is difficult for a worker to hold the tool for an extended period of time in the awkward angles and positions necessary to fully size-reduce the crate. Other disadvantages of using hand tools include managing power cords and vacuum hoses, which become entangled or can act as tripping hazards. In order to improve the crate opening and size-reduction task, Florida International University's Hemispheric Center for Environmental Technology (HCET) is developing a manually operated crate dismantlement system. This versatile system is expected to greatly increase worker efficiency while decreasing fatigue and the possibility of accidents. (authors)

Linear-regression convolutional neural network for fully automated coronary lumen segmentation in intravascular optical coherence tomography

Science.gov (United States)

Yong, Yan Ling; Tan, Li Kuo; McLaughlin, Robert A.; Chee, Kok Han; Liew, Yih Miin

2017-12-01

Intravascular optical coherence tomography (OCT) is an optical imaging modality commonly used in the assessment of coronary artery diseases during percutaneous coronary intervention. Manual segmentation to assess luminal stenosis from OCT pullback scans is challenging and time consuming. We propose a linear-regression convolutional neural network to automatically perform vessel lumen segmentation, parameterized in terms of radial distances from the catheter centroid in polar space. Benchmarked against gold-standard manual segmentation, our proposed algorithm achieves average locational accuracy of the vessel wall of 22 microns, and 0.985 and 0.970 in Dice coefficient and Jaccard similarity index, respectively. The average absolute error of luminal area estimation is 1.38%. The processing rate is 40.6 ms per image, suggesting the potential to be incorporated into a clinical workflow and to provide quantitative assessment of vessel lumen in an intraoperative time frame.

Auxiliary mine ventilation manual

International Nuclear Information System (INIS)

Workplace Safety North