This research aims to support chest computed tomography (CT) medical checkups to decrease the death rate by
lung cancer. We have developed a remote cooperative reading system for lung cancer screening over the Internet, a
secure transmission function, and a cooperative reading environment. It is called the Network-based Reading System. A
telemedicine system involves many issues, such as network costs and data security if we use it over the Internet, which
is an open network. In Japan, broadband access is widespread and its cost is the lowest in the world. We developed our
system considering human machine interface and security. It consists of data entry terminals, a database server, a computer
aided diagnosis (CAD) system, and some reading terminals. It uses a secure Digital Imaging and Communication
in Medicine (DICOM) encrypting method and Public Key Infrastructure (PKI) based secure DICOM image data distribution.
We carried out an experimental trial over the Japan Gigabit Network (JGN), which is the testbed for the Japanese
next-generation network, and conducted verification experiments of secure screening image distribution, some kinds of
data addition, and remote cooperative reading. We found that network bandwidth of about 1.5 Mbps enabled distribution
of screening images and cooperative reading and that the encryption and image distribution methods we proposed
were applicable to the encryption and distribution of general DICOM images via the Internet.
The increasing number of CT images to be interpreted in mass screening requires radiologists to interpret a huge number of CT images, and the capacity for screening has therefore been limited by the capacity to process images. To remedy this situation we considered paramedical staff, especially radiological technologists, as "potential screeners," and investigated their capacity to detect abnormalities in CT images of lung cancer screening with and without the assistance of a computer-aided diagnosis (CAD) system. We then compared their performances with those of physicians. A set of 100 slices of thoracic CT images from 100 cases ( 73 abnormal and 27 normal), one slice per case, was interpreted by 43 paramedical college students. A second interpretation by the students was performed after they had been instructed on how to interpret CT images, and a third interpretation was assisted by a virtual CAD system. We calculated the areas under the ROC curve (Az values) for both students and physicians. For the first set of interpretations, the Az values of 40% out of students placed the Az values within the range of Az values of the physicians, which varied from 0.870 to 0.964. For the second set of interpretations after the students had been instructed on CT image interpretation, the students' rate was 86%, and for the third set of virtual CAD-assisted interpretations it was 95%. The performance of paramedical college students in detecting abnormalities from thoracic CT images proved to be sufficient to qualify them as "potential screeners."
In this paper we present two methods of evaluating the effectiveness of double check (by two radiologists or by a CAD system and a radiologist): One method uses ROC analysis and the other uses the phi correlation coefficient (φ). We used the first method to evaluate the effectiveness of two radiologists conducting double check through discussion (i.e. the radiologists confer; conference system). We used the second method to evaluate the effectiveness of double check in which Reader 2 makes a final assessment by referring to the assessment of Reader 1 (reference system). It is suggested that double check conducted by two radiologists through discussion may not be so effective; however, double check in which Reader 2 makes a final assessment by referring to the assessment or Reader 1 may be very effective. In addition, we discuss problems that may occur in relation to Reader 2 deciding whether to adopt the assessment of Reader 1, and practical models of double check by a CAD system and a radiologist. Continued research is necessary to establish a double check system that improves diagnostic accuracy in practical situations, i.e. it is unknown if assessments are correct.
The objective of this study was to measure the image exploration activity of physicians, and thereby contribute to the development of a support system for CRT image interpretation in thoracic CT screening. In this study, we examined how the pupil diameters of five physicians changes over time during interpretation of a large quantity of CT images on a CRT monitor, and how this might be related to the accuracy of diagnosis. The study showed that, when a large quantity of CT images were viewed through a CRT monitor in a dimly lit room, the pupil diameter decreased during the second half of the long interpretation procedure in three of the five physicians. Furthermore, the pupil diameter frequently became approximately zero because the physician became drowsy. However, when the relationship between these phenomena and the accuracy of diagnosis was analyzed in one of the physicians, proof that such phenomena might lead to statistically significant false negatives or false positives was not found. Despite such results, the potential risk of misdiagnosis cannot be ignored. It may be necessary to devise both equipment and work conditions that will not cause the pupil diameter to become approximately zero during interpretation of images on a CRT monitor.
A recent trend is the automatic screening of color ocular fundus images. The examination of such images is used in the early detection of several adult diseases such as hypertension and diabetes. Since this type of examination is easier than CT, costs less, and has no harmful side effects, it will become a routine medical examination. Normal ocular fundus images are found in more than 90% of all people. To deal with the increasing number of such images, this paper proposes a new approach to process them automatically and accurately. Our approach, based on individual comparison, identifies changes in sequential images: a previously diagnosed normal reference image is compared to a non- diagnosed image.
This paper proposes a new moving-objects tracking method processed by a local spiral labeling with CAM (Content Addressable Memory). The local spiral labeling method was proposed in order to improve one of the shortcomings of TV telephones. The conventional labeling, however, needs huge processing time and a memory capacity in order to compute connecting relations between label numbers. CAM has some functions to search and write the plural contents of the memory at the same time. CAM is suitable for a real time labeling. This paper shows a new labeling algorithm called local spiral labeling, a real-time labeling scheme utilizing CAM, and a prototype system of human head tracking using 0.5 micrometers BiCMOS gate-array technology.