PurposeTo compare non-commercial DICOM toolkits for their de-identification ability in removing a patient's personal health information (PHI) from a DICOM header.Materials and MethodsTen DICOM toolkits were selected for de-identification tests. Tests were performed by using the system’s default de-identification profile and, subsequently, the tools' best adjusted settings. We aimed to eliminate fifty elements considered to contain identifying patient information. The tools were also examined for their respective methods of customization.ResultsOnly one tool was able to de-identify all required elements with the default setting. Not all of the toolkits provide a customizable de-identification profile. Six tools allowed changes by selecting the provided profiles, giving input through a graphical user interface (GUI) or configuration text file, or providing the appropriate command-line arguments. Using adjusted settings, four of those six toolkits were able to perform full de-identification.ConclusionOnly five tools could properly de-identify the defined DICOM elements, and in four cases, only after careful customization. Therefore, free DICOM toolkits should be used with extreme care to prevent the risk of disclosing PHI, especially when using the default configuration. In case optimal security is required, one of the five toolkits is proposed.Key Points• Free DICOM toolkits should be carefully used to prevent patient identity disclosure.• Each DICOM tool produces its own specific outcomes from the de-identification process.• In case optimal security is required, using one DICOM toolkit is proposed.

Persaingan industri perbankan saat ini semakin meningkat, baik dalam hal penyediaan inovasi produk serta peningkatan kualitas transaksi dan pelayanan. Untuk mengatasi masalah tersebut diciptakan sebuah terminal yang dikenal dengan ATM. Namun fungsionalitas dan efektifitas ATM tersebut belum memenuhi kebutuhan nasabah dikarenakan pengambilan keputusan penentuan lokasi ATM belum menggunakan SPK sehingga banyak kriteria yang terlupakan dalam penentuan lokasi ATM terbaik. Metode AHP yang merupakan sebuah hierarki fungsional dengan input utamanya adalah persepsi manusia sedangkan metode SAW dengan konsep dasar mencari penjumlahan terbobot dari rating kinerja pada setiap alternatif pada semua atribut. AHP digunakan untuk memberikan pembobotan pada masing-masing kriteria dan SAW untuk melakukan perangkingan dari masing-masing alternatif. Terdapat 7 kriteria dengan 11 sub kriteria pada pembobotan dan 76 data alternatif. Pengujian dilakukan dengan membandingkan hasil delpoyment ATM dengan hasil perhitungan sistem. Dari 76 data alternatif yang diujikan, terdapat 38 lokasi deployment ATM. Dari hasil pengujian yang ditampilkan dalam confusion matrix, pada kriteria yang tidak teruji signifikansi didapatkan 33 data True Positive, 38 True Negative, 5 False Negative dan 5 False Positive dengan akurasi sebesar 86,84%, dan pada kriteria yang teruji signifikansi didapatkan 35 data True Positive, 35 True Negative, 3 False Negative dan 3 False Positive memiliki akurasi 92,11%.

ObjectivesReproducibility of myocardial contour determination in cardiac magnetic resonance imaging is important, especially when determining T2* values per myocardial segment as a prognostic factor of heart failure or thalassemia. A method creating a composite image with contrasts optimized for drawing myocardial contours is introduced and compared with the standard method on a single image.Materials and methodsA total of 36 short-axis slices from bright-blood multigradient echo (MGE) T2* scans of 21 patients were acquired at eight echo times. Four observers drew free-hand myocardial contours on one manually selected T2* image (method 1) and on one image composed by blending three images acquired at TEs providing optimum contrast-to-noise ratio between the myocardium and its surrounding regions (method 2).ResultsMyocardial contouring by method 2 met higher interobserver reproducibility than method 1 (P < 0.001) with smaller Coefficient of variance (CoV) of T2* values in the presence of myocardial iron accumulation (9.79 vs. 15.91 %) and in both global myocardial and mid-ventricular septum regions (12.29 vs. 16.88 and 5.76 vs. 8.16 %, respectively).ConclusionThe use of contrast-optimized composite images in MGE data analysis improves reproducibility of myocardial contour determination, leading to increased consistency in the calculated T2* values enhancing the diagnostic impact of this measure of iron overload.

Retinal blood vessels can give information about abnormalities or disease by examining its pathological changes. One abnormality is diabetic retinopathy, characterized by a disorder of retinal blood vessels resulting from diabetes mellitus. Currently, diabetic retinopathy is one of the major causes of human vision abnormalities and blindness. Hence, early detection can lead to proper treatment, and segmentation of the abnormality provides a map of retinal vessels that can facilitate the assessment of the characteristics of these vessels. In this paper, the authors propose a new method, consisting of a sequence of procedures, to segment blood vessels in a retinal image. In the method, attribute filtering with a so-called Max-Tree is used to represent the image based on its gray value. The filtering process is done using the branches filtering approach in which the tree branches are selected based on the non-compactness of the nodes. The selection is started from the leaves. This experiment was performed on 40 retinal images, and utilized the manual segmentation created by an observer to validate the results. The proposed method can deliver an average accuracy of 94.21%.

To investigate possible de-identification methodologies within the Cross-Enterprise Document Sharing for imaging (XDS-I) environment in order to provide strengthened support for image data exchange as part of clinical research projects. De-identification, using anonymization or pseudonymization, is the most common method to perform information removal within DICOM data. However, it is not a standard part of the XDS-I profiles. Different methodologies were observed to define how and where de-identification should take place within an XDS environment used for scientific research. De-identification service can be placed in three locations within the XDS-I framework: 1) within the Document Source, 2) between the Document Source and Document Consumer, and 3) within the Document Consumer. First method has a potential advantage with respect to the exposure of the images to outside systems but has drawbacks with respect to additional hardware and configuration requirements. Second and third method have big concern in exposing original documents with all identifiable data being intact after leaving the Document Source. De-identification within the Document Source has more advantages compared to the other methods. On the contrary, it is less recommended to perform de-identification within the Document Consumer since it has the highest risk of the exposure of patients identity due to the fact that images are exposed without de-identification during the transfers.

To produce competent and professional lecturers, of course, requires various efforts so that these goals are achieved, one of the efforts that can be made is through lecturer performance appraisal. At Tabanan University, lecturer performance assessment is carried out at the end of each semester, but in its implementation there are obstacles, namely: the results of the assessment are still not appropriate because they only assess education and learning criteria and and does not include any other defining criteria, besides that in Tabanan University, does not yet have a benchmark for determining lecturer performance. This has an impact on the decision-making process in evaluating and ranking lecturer performance. Therefore, to overcome these obstacles, a decision support system (DSS) is needed. The DSS was built using a combination of the Profile Matching and TOPSIS methods. The Profile Matching method is used in the weighting process and the calculation of the level of suitability of each alternative, while the TOPSIS method is for ranking calculations. The decision support system is built using four criteria that are taken from the employee performance targets.. These criteria are: Education and Teaching, Research, Community Service and Work Behavior.

ObjectivesTo present an adapted Clinical Trial Processor (CTP) test set-up for receiving, anonymising and saving Digital Imaging and Communications in Medicine (DICOM) data using external input from the original database of an existing clinical study information system to guide the anonymisation process.MethodsTwo methods are presented for an adapted CTP test set-up. In the first method, images are pushed from the Picture Archiving and Communication System (PACS) using the DICOM protocol through a local network. In the second method, images are transferred through the internet using the HTTPS protocol.ResultsIn total 25,000 images from 50 patients were moved from the PACS, anonymised and stored within roughly 2 h using the first method. In the second method, an average of 10 images per minute were transferred and processed over a residential connection. In both methods, no duplicated images were stored when previous images were retransferred. The anonymised images are stored in appropriate directories.ConclusionsThe CTP can transfer and process DICOM images correctly in a very easy set-up providing a fast, secure and stable environment. The adapted CTP allows easy integration into an environment in which patient data are already included in an existing information system.Key PointsStore DICOM images correctly in a very easy set-up in a fast, secure and stable environmentAllows adaptation of the software to perform a certain task based on specific needsAllows easy integration into an existing environmentReduce the possibility of inappropriate anonymisation

A proper test migration is a crucial step in the PACS transition process, which can eliminate many of the problems in the actual migration. However, with any migration, there has to be a willingness to take a limited amount of risk since not all problems can nor will be identified in the test migration.