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Biomedical subjects

Junji Morishita

Publications and source records attributed to Junji Morishita.

11 recordsLinked to original sources

[Application of phase contrast imaging to mammography].

Phase contrast images were obtained experimentally by using a customized mammography unit with a nominal focal spot size of 100 microm and variable source-to-image distances of up to 1.5 m. The purpose of this study was to examine the applicability and potential usefulness of phase contrast imaging for mammography. A mammography phantom (ACR156 RMI phantom) was imaged, and its visibility was examined. The optical density of the phantom images was adjusted to approximately 1.3 for both the contact and phase contrast images. Forty-one observers (18 medical doctors and 23 radiological technologists) participated in visual evaluation of the images. Results showed that, in comparison with the images of contact mammography, the phantom images of phase contrast imaging demonstrated statistically significantly superior visibility for fibers, clustered micro-calcifications, and masses. Therefore, phase contrast imaging obtained by using the customized mammography unit would be useful for improving diagnostic accuracy in mammography.

Humans↗

Investigation of misfiled cases in the PACS environment and a solution to prevent filing errors for chest radiographs.

RATIONALE AND OBJECTIVE: The aim of the study was to survey misfiled cases in a picture archiving and communication system environment at two hospitals and to demonstrate the potential usefulness of an automated patient recognition method for posteroanterior chest radiographs based on a template-matching technique designed to prevent filing errors. MATERIALS AND METHODS: We surveyed misfiled cases obtained from different modalities in one hospital for 25 months, and misfiled cases of chest radiographs in another hospital for 17 months. For investigating the usefulness of an automated patient recognition and identification method for chest radiographs, a prospective study has been completed in clinical settings at the latter hospital. RESULTS: The total numbers of misfiled cases for different modalities in one hospital and for chest radiographs in another hospital were 327 and 22, respectively. The misfiled cases in the two hospitals were mainly the result of human errors (eg, incorrect manual entries of patient information, incorrect usage of identification cards in which an identification card for the previous patient was used for the next patient's image acquisition). The prospective study indicated the usefulness of the computerized method for discovering misfiled cases with a high performance (ie, an 86.4% correct warning rate for different patients and 1.5% incorrect warning rate for the same patients). CONCLUSION: We confirmed the occurrence of misfiled cases in the two hospitals. The automated patient recognition and identification method for chest radiographs would be useful in preventing wrong images from being stored in the picture archiving and communication system environment.

Database Management Systems↗

Evaluation of edge effect due to phase contrast imaging for mammography.

It is well-known that the edge effect produced by phase contrast imaging results in the edge enhancement of x-ray images and thereby sharpens those images. It has recently been reported that phase contrast imaging using practical x-ray tubes with small focal spots has improved image sharpness as observed in the phase contrast imaging with x-ray from synchrotron radiation or micro-focus x-ray tubes. In this study, we conducted the phase contrast imaging of a plastic fiber and plant seeds using a customized mammography equipment with a 0.1 mm focal spot, and the improvement of image sharpness was evaluated in terms of spatial frequency response of the images. We observed that the image contrast of the plastic fiber was increased by edge enhancement, and, as predicted elsewhere, spectral analysis revealed that as the spatial frequencies of the x-ray images increased, so did the sharpness gained through phase contrast imaging. Thus, phase contrast imaging using a practical molybdenum anode tube with a 0.1 mm-focal spot would benefit mammography, in which the morphological detectability of small species such as microcalcifications is of great concern. And detectability of tumor-surrounded glandular tissues in dense breast would be also improved by the phase contrast imaging.

Algorithms↗

Potential usefulness of biological fingerprints in chest radiographs for automated patient recognition and identification.

RATIONALE AND OBJECTIVES: The purpose of this study was to demonstrate the potential usefulness of "biological fingerprints" in chest radiographs for automated patient recognition and identification. MATERIALS AND METHODS: Thoracic fields, cardiac shadows, the superior mediastinum, lung apices, a part of the right lung, and the right lower lung that includes the costophrenic angle were used as biological fingerprints in chest radiographs. Each of the biological fingerprints in a current chest radiograph was used as a template for determination of the correlation value with the corresponding biological fingerprint in a previous chest radiograph for patient recognition and identification. The overall performance of the method developed was examined in terms of receiver operating characteristic curves. RESULTS: Receiver operating characteristic curves obtained with different biological fingerprints, except for the part of the right lung, indicated a high performance in identifying patients. These results showed that a new concept of biological fingerprints in radiologic images would be useful in patient recognition and identification. The low performance with the part of the right lung seems to be related to a general observation that this region does not usually include features unique to a specific patient. The performance of the artificial neural networks by use of a combination of five biological fingerprints was higher than results obtained with each biological fingerprint. CONCLUSION: The use of automated patient identification based on biological fingerprints in chest radiographs is promising for helping to discover misfiled patient images, especially in a picture archiving and communication system environment.

Dermatoglyphics↗

[Development of an automated patient-recognition method for digital chest radiographs using edge-enhanced images].

It is important that all images in a picture archiving and communication system (PACS) environment should be stored in the correct location, e.g., in the proper patient's folder. However, if patient information, such as identification number or patient name, has been entered incorrectly, the image may be stored in the wrong place. We are developing an automated patient recognition method for chest radiographs based on a template-matching technique to prevent such filing errors. To further improve the performance of our method, we investigated the usefulness of a new automated patient-recognition method based on a template-matching technique by using edge-enhanced and smoothed images. We found that the relationship between the correlation values obtained with and without the edge-enhancement technique tended to provide different criteria for identifying correct or incorrect patients. When we combined the two methods to distinguish the images by a rule-based method, 67.1% of wrongly identified patients in our database could be identified as wrongly identified, without any false warnings for correctly identified patients. We consider that this automated method for patient recognition based on edge-enhanced images would be useful in preventing "wrong" images from being stored in a PACS environment.

Databases, Factual↗