The distance-based outlier detection method detects the implied outliers by calculating the distance of the points in the dataset, but the computational complexity is particularly high when processing multidimensional...The distance-based outlier detection method detects the implied outliers by calculating the distance of the points in the dataset, but the computational complexity is particularly high when processing multidimensional datasets. In addition, the traditional outlier detection method does not consider the frequency of subsets occurrence, thus, the detected outliers do not fit the definition of outliers (i.e., rarely appearing). The pattern mining-based outlier detection approaches have solved this problem, but the importance of each pattern is not taken into account in outlier detection process, so the detected outliers cannot truly reflect some actual situation. Aimed at these problems, a two-phase minimal weighted rare pattern mining-based outlier detection approach, called MWRPM-Outlier, is proposed to effectively detect outliers on the weight data stream. In particular, a method called MWRPM is proposed in the pattern mining phase to fast mine the minimal weighted rare patterns, and then two deviation factors are defined in outlier detection phase to measure the abnormal degree of each transaction on the weight data stream. Experimental results show that the proposed MWRPM-Outlier approach has excellent performance in outlier detection and MWRPM approach outperforms in weighted rare pattern mining.展开更多
Purpose: With usually a millimeter-level PTV margin, stereotactic radiosurgery (SRS) and stereotactic body radiation therapy (SBRT) pose a stringent requirement on the isocentricity of the Linac. This requirement is p...Purpose: With usually a millimeter-level PTV margin, stereotactic radiosurgery (SRS) and stereotactic body radiation therapy (SBRT) pose a stringent requirement on the isocentricity of the Linac. This requirement is partly fulfilled by routine isocenter quality assurance (QA) test to verify the size and location of the isocenter. The current common QA methods such as spoke shot were developed before SBRT/SRS became popular and when IGRT was largely absent and hence have their limitations. In this work, we describe an isocenter QA approach based on portal imaging to provide the community with a superior alternative. Methods: The proposed approach utilizes a BrainLab ball bearing (BB) phantom in conjunction with an electronic portal imaging devices (EPID) imager. The BB phantom was first aligned with a calibrated room laser system. Portal images were then acquired using 6 MV beam with a 2 × 2 cm2 open field and a 15 mm cone on a Varian TrueBeam STx machine. The gantry, collimator, and table were rotated separately at selected angles to acquire a series of portal images in order to determine the isocenter of each rotating system. The location and diameter of these isocenters were determined by calculating the relative displacement of either BB or open field edge between the acquired EPID images. The demonstration of the reproducibility and robustness of this EPID-based approach was carried out by repeating measurements 10 times independently for each rotating system and simulating clinical scenarios of asymmetric jaws and misalignment of BB phantom, respectively. Results: For our TrueBeam STx machine, the isocenter diameter derived from open-field EPID images was roughly 0.15 mm, 0.18 mm, 0.49 mm for the collimator, table, and gantry, respectively. For the collimator and gantry, images taken with the cone gave considerably smaller isocenter diameter. Results remained almost unchanged despite the presence of simulated BB misalignment and asymmetric jaws error, and between independent measurements. Isocenter location and diameter derived from images obtained at a limited number of angles (≤11) were adequately accurate to represent those derived from images of densely sampled angles. Conclusions: An EPID-based isocenter QA approach is described and demonstrated to be accurate, robust, and reproducible. This approach provides a superior alternative to conventional isocenter QA methods with no additional cost. It can be implemented with convenience for any linear accelerator with an EPID imager.展开更多
Purpose: The objective of this study is to investigate the properties of I’mRT MatriXX device in electron beams, and to validate MatriXX in electron dosimetry and quality assurance (QA). Methods: The measurements wer...Purpose: The objective of this study is to investigate the properties of I’mRT MatriXX device in electron beams, and to validate MatriXX in electron dosimetry and quality assurance (QA). Methods: The measurements were conducted using MatriXX in electron and photon beams from Siemens linacs. The MatriXX was placed horizontally on the linac tabletop. Solid Water layers were used for buildup. For all the measurements, the linac gantry angle was 0?, and the source-to-surface distance was100 cmfrom the Solid Water surface. The electron cone factors, cutout factors, and beam profiles were measured and compared with thimble ionization chamber results. Results: The effective water equivalent depth of MatriXX measurement point is larger than4 mm. When measuring at the respective depths of maximum dose, MatriXX has different responses to different beam energies. The cone factors measured by MatriXX are nearly identical or close to those derived by ionization chambers. Beam profiles (flatness and symmetry) can be easily determined using MatriXX and are comparable to water tank results. The planar dose map of electron cutout blocks can be visually observed, and the cutout factors can be conveniently measured. Conclusions: The MatriXX needs separate dose calibration factors for electron and photon beams. MatriXX can be used to measure electron cutout factors and beam profiles, thus has the potentials in electron beam dosimetry and routine linac and patient-specific QA tests.展开更多
Diabetic retinopathy(DR)is an important cause of blindness globally,and its prevalence is increasing.Early detection and intervention can help change the outcomes of the disease.The rapid development of artificial int...Diabetic retinopathy(DR)is an important cause of blindness globally,and its prevalence is increasing.Early detection and intervention can help change the outcomes of the disease.The rapid development of artificial intelligence(AI)in recent years has led to new possibilities for the screening and diagnosis of DR.An AI-based diagnostic system for the detection of DR has significant advantages,such as high efficiency,high accuracy,and lower demand for human resources.At the same time,there are shortcomings,such as the lack of standards for development and evaluation and the limited scope of application.This article demonstrates the current applications of AI in the field of DR,existing problems,and possible future development directions.展开更多
基金supported by Fundamental Research Funds for the Central Universities (No. 2018XD004)
文摘The distance-based outlier detection method detects the implied outliers by calculating the distance of the points in the dataset, but the computational complexity is particularly high when processing multidimensional datasets. In addition, the traditional outlier detection method does not consider the frequency of subsets occurrence, thus, the detected outliers do not fit the definition of outliers (i.e., rarely appearing). The pattern mining-based outlier detection approaches have solved this problem, but the importance of each pattern is not taken into account in outlier detection process, so the detected outliers cannot truly reflect some actual situation. Aimed at these problems, a two-phase minimal weighted rare pattern mining-based outlier detection approach, called MWRPM-Outlier, is proposed to effectively detect outliers on the weight data stream. In particular, a method called MWRPM is proposed in the pattern mining phase to fast mine the minimal weighted rare patterns, and then two deviation factors are defined in outlier detection phase to measure the abnormal degree of each transaction on the weight data stream. Experimental results show that the proposed MWRPM-Outlier approach has excellent performance in outlier detection and MWRPM approach outperforms in weighted rare pattern mining.
文摘Purpose: With usually a millimeter-level PTV margin, stereotactic radiosurgery (SRS) and stereotactic body radiation therapy (SBRT) pose a stringent requirement on the isocentricity of the Linac. This requirement is partly fulfilled by routine isocenter quality assurance (QA) test to verify the size and location of the isocenter. The current common QA methods such as spoke shot were developed before SBRT/SRS became popular and when IGRT was largely absent and hence have their limitations. In this work, we describe an isocenter QA approach based on portal imaging to provide the community with a superior alternative. Methods: The proposed approach utilizes a BrainLab ball bearing (BB) phantom in conjunction with an electronic portal imaging devices (EPID) imager. The BB phantom was first aligned with a calibrated room laser system. Portal images were then acquired using 6 MV beam with a 2 × 2 cm2 open field and a 15 mm cone on a Varian TrueBeam STx machine. The gantry, collimator, and table were rotated separately at selected angles to acquire a series of portal images in order to determine the isocenter of each rotating system. The location and diameter of these isocenters were determined by calculating the relative displacement of either BB or open field edge between the acquired EPID images. The demonstration of the reproducibility and robustness of this EPID-based approach was carried out by repeating measurements 10 times independently for each rotating system and simulating clinical scenarios of asymmetric jaws and misalignment of BB phantom, respectively. Results: For our TrueBeam STx machine, the isocenter diameter derived from open-field EPID images was roughly 0.15 mm, 0.18 mm, 0.49 mm for the collimator, table, and gantry, respectively. For the collimator and gantry, images taken with the cone gave considerably smaller isocenter diameter. Results remained almost unchanged despite the presence of simulated BB misalignment and asymmetric jaws error, and between independent measurements. Isocenter location and diameter derived from images obtained at a limited number of angles (≤11) were adequately accurate to represent those derived from images of densely sampled angles. Conclusions: An EPID-based isocenter QA approach is described and demonstrated to be accurate, robust, and reproducible. This approach provides a superior alternative to conventional isocenter QA methods with no additional cost. It can be implemented with convenience for any linear accelerator with an EPID imager.
文摘Purpose: The objective of this study is to investigate the properties of I’mRT MatriXX device in electron beams, and to validate MatriXX in electron dosimetry and quality assurance (QA). Methods: The measurements were conducted using MatriXX in electron and photon beams from Siemens linacs. The MatriXX was placed horizontally on the linac tabletop. Solid Water layers were used for buildup. For all the measurements, the linac gantry angle was 0?, and the source-to-surface distance was100 cmfrom the Solid Water surface. The electron cone factors, cutout factors, and beam profiles were measured and compared with thimble ionization chamber results. Results: The effective water equivalent depth of MatriXX measurement point is larger than4 mm. When measuring at the respective depths of maximum dose, MatriXX has different responses to different beam energies. The cone factors measured by MatriXX are nearly identical or close to those derived by ionization chambers. Beam profiles (flatness and symmetry) can be easily determined using MatriXX and are comparable to water tank results. The planar dose map of electron cutout blocks can be visually observed, and the cutout factors can be conveniently measured. Conclusions: The MatriXX needs separate dose calibration factors for electron and photon beams. MatriXX can be used to measure electron cutout factors and beam profiles, thus has the potentials in electron beam dosimetry and routine linac and patient-specific QA tests.
基金This work was supported by grants from the Chinese National Natural Science Foundation(No.82071012)The Project of Shanghai Shen Kang Hospital Development Centre(Nos.SHDC2020CR30538 and SHDC2018110)+3 种基金Shanghai Engineering Research Center of Precise Diagnosis and Treatment of Eye Diseases,Shanghai,China(No.19DZ2250100)The Science and Technology Commission of Shanghai Municipality(No.20DZ1100200)Shanghai Public Health System Three-Year Plan-Key Subjects(No.GWV10.1-XK7)Shanghai General Hospital,Clinical Research(CTCCR-2018Z01)。
文摘Diabetic retinopathy(DR)is an important cause of blindness globally,and its prevalence is increasing.Early detection and intervention can help change the outcomes of the disease.The rapid development of artificial intelligence(AI)in recent years has led to new possibilities for the screening and diagnosis of DR.An AI-based diagnostic system for the detection of DR has significant advantages,such as high efficiency,high accuracy,and lower demand for human resources.At the same time,there are shortcomings,such as the lack of standards for development and evaluation and the limited scope of application.This article demonstrates the current applications of AI in the field of DR,existing problems,and possible future development directions.
