A Web-based Integrated Medical Information System for Telepathology

Transcription

1 SCIS & ISIS 2010, Dec. 8-12, 2010, Okayama Convention Center, Okayama, Japan A Web-based Integrated Medical Information System for Telepathology Thitaphan Jongsataporn 1, Surapun Yimmun 5 1,5 Department of Industrial Physics and Medical Instrumentation, Faculty of Applied Science, King Mongkut s University of Technology North Bangkok, Bangkok, Thailand. hpong11@hotmail.com, sym_imi@yahoo.com Piyamas Suapang 2 2 Department of Physics, Faculty of Science, Rangsit University, Pathumthani, Thailand. piyamas@rsu.ac.th, piyamas_suapang@yahoo.com Rodjarin Boontawan 3, Kobchai Dejhan 4 3,4 Department of Telecommunications Engineering, Faculty of Engineering, King Mongkut s Institute of Technology Ladkrabang, Bangkok, Thailand. rodjarinb@yahoo.com, kobchai@telecom.kmitl.ac.th Abstract The design and implementation of A Web-based Integrated Medical Information System for Telepathology which server was developed using software such as Borland C++ Builder 5.0, PHP and MySQL for image archive, image compression, image processing and image transmission. The system provides the following facilities: (1) DICOM-format image archive. (2) Medical Image Compression based on JPEG and JPEG2000. and (3) DICOM viewer. The results shown that (1) our system can also convert the image data both single frame and multiframe in normal or automatic DICOM process into the standard DICOM 3.0 format without altering the image data. (2) The resulting images are then compressed with two different techniques JPEG and JPEG2000. The significant advantage of JPEG2000 over normal JPEG is that the error from JPEG2000 compression is smaller than the error from JPEG. Nevertheless, both methods share a similar mishap; when the compression ratio increases, they both generate more error than the processes on lower compression ratio. And (3) our system can open single frame and continuous frames, each of which can exhibit information in.dcm file format with no distortion and digital image processing based on local contrast enhancement, adaptive interpolators techniques and cine loop. The system has been developed and provided medical image services over long distance which showed the usefulness of our approach. Keywords-Image Archive, Image Compression, Image Processing, DICOM Standard, Telepathology I. INTRODUCTION Telepathology system can be defined as basically the viewing of pathological specimens on monitor. There are two main types of telepathology. The first one is called Dynamic Imaging Telepathology, which is also known as Real Time Video Imaging. During DI telepathology a microscope is used along with a personal computer to send images. This method is very beneficial because it is almost as the same as the usual technique of pathological examinations. The second type of telepathology is the Static Imaging Telepathology. In this form, pathologists select images, store them on a computer, and upload the image to other pathologists. Although this may seem practical, there are two main downsides to SI Telepathology. For one, only a small number of images can be transmitted, and two, the consulting telepathologist is unable to select the images he wants transmitted. Although much more convenient, both types of telepathology have many disadvantages. Image quality is often an eminent problem, and often times, it is hard for pathologists to make diagnosis due to the poor quality of the image. In today s health care system, there are many uses of telepathology. One is to, provide urgent services at sites either without a pathologist or with a pathologist requiring back- up. Secondly, telepathology can, Provide immediate access to subspecialty pathology consultants. For example, if a primary care physician in a rural area needs a pathologist to diagnose a disease, and the nearest pathologist is over an hour away, telemedicine can be an excellent alternative. Thirdly, and probably the one most often used, is to, generate second opinions. Often times, physicians are not sure if their diagnosis is correct and in order to confirm their decision, they can contact another telepathologist via telemedicine. Additionally, it can, assist pathologists in completing or refining a differential diagnosis. And finally, telepathology can be used to, continue medical education, proficiency, testing, and recertification of pathologists as well as other laboratory personnel. This can be extremely beneficial to students in rural areas. This way, they do not have to travel far to receive their education or take exams. Obviously, telepathology has become an important aspect of telemedicine in the past few years and it will even more in the years to come. With the advent of computer and communication technologies, construction of an effective telepathology system becomes possible [1]. Nowadays, Digital Image and Communication in Medicine (DICOM) has created to be the standard of Picture Archiving 1139

2 and Communication System (PACS) for exchanging the imaging data and information. Additional, the size of most medical images are large which will need to be compressed before sending or collecting data because of the limited of the band width and also limited capacity of the data saving space [2]. Therefore, compression technology in PACS is more important part than any part in store or transmission. Additional, JPEG is an international standard for lossy, lossless, and nearly lossless compression of continuous-tone still image and is the primary compression technology supported in DICOM. In December 1999, a draft version of a new international standard for image compression based on wavelet technology was completed. The new standard is officially known as the JPEG2000 image coding system. II. METHODOLOGY A. Image Acquisition and Capture This research has done with collecting the imaging data by selecting the data from endoscope camera by using video capture card (model: Scholly smartbox) processing through AVICAP Windows Class. These function as the interface between Application and Device Driver to control the image receiver to collect the image signal in single frame or multiframe windows bitmap file (.BMP) type and continuous frame in.avi. In connection with endoscope camera system with digital USB 2.0 output and PC 2 GHz or more. professional fields. Standard number has form of "PS 3.X- YYYY". Here, X is a part number and YYYY is publication year. For example, DICOM Part 2 is "Conformance" and document number "PS ". DICOM standard rules are divided into 16 parts [3]. 1) DICOM Information Object Definition DlCOM specifies that image information represents an Information Object which is defined in Information Object Definition (IOD) as shown in Figure 3 [4], and commanding word is relating to Service Class which is defined in DICOM Message Service Element (DIMSE). IOD specify information for medical image where is corresponding to patient's name, examination type, date and it looks like a format dealing with standardized medical information. With these items, if there are real values on each item, it is called Information Object instance. Fig. 3 Information Object Definition (IOD) Model. 2) Data Element Fig. 1 The interface between Application and Device Driver. Fig. 2 Collecting the imaging data by using video capture card. B. DICOM DICOM is a standard, which has been developed by ACR/NEMA. The ACR is the American College of Radiology and NEMA is the National Electrical Manufacturers Association. This standard allows different manufacturers equipment to communicate. For example, all CT images will be stored in the same format irrespective of manufacturer and the header information pertaining to the CT images will also be in the same format irrespective of whose device generated the image. The early standard is focus on viewing data between each other dissimilar companies based on point-topoint connection. But, DlCOM standard with rapid development of computer network and PACS is used present through the concept controlling information in network standards. Because DlCOM standard was strong adaptability, it is necessary to adopt DICOM standard in several Fig. 4 DICOM as standard of image format. DlCOM communicates each attribute as shown in Figure 4. One data element communicates one attribute, and several data element should be necessary for IOD instance whole. That is, several data element must be combined as shown in Figure 3 to make any person IOD instance. One data element's details structure of them is a form in Figure 3 or 5(a) lower columns. Tag (0010, 0020) here is consisted of two integers representing patient's ID. VR (value representation) specify the characteristics of information. Sometimes VR may be omitted. The value length is the number that displays how much length of data in value field and value field corresponds to data actually. If value field is a name (date), it can be represented as PN (DA). Here, PN 1140

3 means the patient name and DA means date. Figure 5 describes the example for data element of any tag. Value field used often like patient's name may understand even if do not clarify PN. It is known that this is implicit VR. Because patient's name corresponds to implicit VR, it is same effective on the results for transmission. Otherwise, we are called explicit VR in the case of whether we should inform the information characteristics. (a) (b) Fig. 5 A description of data element. (a) components (b) an example of a specific tag. The steps of DICOM-format image archive has shown in Figure 6. the original imaging data based on the JPEG and JPEG2000 image compressing standard. 1) JPEG The JPEG [6][7][8] standard for image compression is comprised of a toolkit that has three distinct components: baseline lossy, extended lossy, and lossless. Baseline lossy JPEG, the most widely implemented of the three, utilizes the discrete cosine transform (DCT) to decompose an image into sets of spatial frequency coefficients. Figure 7 [6] show the main procedure for all DCT-base encoding and decoding processes, The DCT is done on an 8x8 pixel block-adaptive basis. Baseline lossy JPEG supports 8 bits-per-pixel source imagery, offers a simple quantization scheme that enables users of the algorithm to trade off the degree of file size reduction, i.e., compression ratio, with image quality, and utilizes sequential Huffman entropy coding. Extended lossy JPEG is also based on the 8x8 pixel block adaptive DCT. Fig. 6 The steps of data transformation to DICOM format. Firstly, analysis and type selecting of data which to analyze whether raw (input) data be compressed or other archive, and then separate the data by text data such patient s curing history and binary code data such image data from medical instrumentation. Secondly, additional text data for user to adding which important to the original image not have curing history or data. Thirdly, decoding text data from the first step to the stimulation (model) of DICOM format by sending the tag number into encoding module from (respective number) first to end which image data on the last place. Finally, decoding into DICOM format taking the tag number from the third step to compare with standard dictionary program, and then get the value (number) for encoding to absolutely data element. C. Image Compression A medical image requires very high quality unlike an image that is used usually. For example, a chest image that is acquired in CR amounts one image size to 7-8 MB. Like this, when an image acquiring from various equipments is deciphered by interpretation doctor or stores for conservation to long term storage device etc., it should be compressed in extent that do not influence on next interpretation. Therefore, compression technology in PACS is more important part than any part in store or transmission. In DICOM standard, the compression technology specify in lossy or lossless methods such as JPEG, run-length encoding, or JPEG-LS. Currently, JPEG2000 in [5] is added in new standard of DICOM image compression. Thus, compress Fig. 7 DCT-based encoder and decoder simplified diagram. 2) JPEG2000 JPEG2000 [9][10] characteristic can embody lossy and lossless compression at the same time in one encoded bit stream, and is shown quality of more excellently eminent image than existent JPEG in high compressibility. In addition, JPEG2000 in a sense of ROI (region of interest) coding is possible, and can be applied to technique of watermarking, labeling etc. for security of image. Also, it has various bit depth to 1 bit through 16 bits in compression and supports compression of motion image. Figure 8 [10], shows a biock diagram for JPEG2000 algorithm. The strength of JPEG2000 is that it is capable of tiling unlike JPEG (Figure 9) [10]. Since JPEG processes 8x8 subimage tiling and DCT (discrete cosine transform), it is tended to block shape artifact in high compression ratio, On the other hand, JPEG2000 is advantage that can enhance quality of image or reduce use of memory controlling by tiling of image random. Also, DCT in JPEG changes an image to characteristic of frequency, but JPEG2000 is scalable to an image by scale or resolution because DWT (discrete wavelet transform). Recently, moving picture compression of medical image was discussed at MPEG in 2002 but that issue was not decided yet as DICOM base standard in 2003 apart Moving picture 1141

4 present in PACS means that first several still image were captured, multiframe DICOM images were generated followed by animated. whilst the Meta information is stored in the database. This gives a dual benefit: 1) Fast query of the Meta information as the data is stored in the database. 2) Fast access to pixel data given that the pixel data is stored on the file system and file IO performance can be maximized when the CPU is busy processing the meta information. Fig. 8 A block diagram for JPEG 2000 (a) encoder, (b) decoder. Fig. 9 Tiling, DC level shifting and DWT of each image tile component. D. Overview of A Web-based Integrated Medical Information System for Telepathology Component of a Web-based Integrated Medical Information System for Telepathology can be used by the various modalities for reusable storage. The medical database storage component can be considered to be made up of two parts: 1) Data Access Layer 2) The underlying storage media. The medical database storage component exposes its functionality through the data access layer. The data access layer of the medical database repository implements a published set of data access interfaces to store, retrieve, modify and query the data present in the underlying repository. These interfaces are concerned with access and transfer of medical data. The data access layer abstracts the underlying storage media, which in our case happens to be a commercially available DBMS from the client. The architecture of the reusable medical database component gives a provision where in the lowest layer, which accesses the storage media, can be a plug-in component in itself. This gives a provision for various modalities to plug in their specific storage accessing mechanism based on the commercial off the shelf database they opt as shown in figure 10. In addition to the performance tuning done at the DBMS level, it is also important that the data access layer is designed for good performance. One of the key high performance use cases of any medical database is the fast rendering of a medical image. Medical images contain pixel data and it is very important to ensure that this pixel data is stored for extremely easy and fast access. In our database component, the pixel data is stored in a separate file on the file system Fig. 10 Modality specific Plug-in. Medical images comprise of pixel data. This pixel data can be stored by modalities on different hardware configurations. The architecture of medical database storage component gives a provision where in the modality could choose to plug-in its own pixel handling plug-in. As with off the shelf databases, the component is provided with a default implementation of the pixel plug-in which can readily deployed on a Windows based operating system in any modality. The component also has the provision of working with customized schemas in a modality. As noted earlier, certain modality might already have an existing schema on which certain specific applications (like for e.g. reporting) might be using. In such situations, in order to make our component work with modality private schema, Database Views are used. The modality owners can then provide the mapping from views to private tables. Having a provision for the modality to develop their own accessor plug-in component that understands the underlying schema for storing data provides this flexibility. Medical images stored in the DICOM format would contain redundant information. For example, let us say 10 images are acquired out of a endoscope camera. Each of these 10 images in the DICOM format will contain the same information with respect to the patient details such as patient name, patient Id, birth date, and study date, study time, series modality information. It is good to avoid this redundancy and for this the data must be normalized and stored in the repository. On normalization, the patient information, which is identical in all the DICOM files, is stored as a single entity in the Patient table in the database. Similarly, the study and series information, which are identical in all the DICOM files are stored as just two entities in the respective Study and Series tables. 1142

5 III. RESULTS AND DISCUSSION To control the image capturing through the image capturing device, the program can connect to the hardware and bring video signals from endoscope camera. Then collect the imaging data from the video signal. The collection was sent to the single frame and multiframe in Windows Bitmap file format (.BMP) and continuous frame.avi which without changing of image shape. For converting data to the DICOM data construction, the program can convert the data to the DICOM data construction after both various image collecting process and also automatic image collecting by converting without changing the image point data or not changing any the image data in the process. The image compression, the program can compress from collect the imaging data in single frame file format and multiframe file format before compress to JPEG and JPEG2000 by having the same compressing ratio. The significant advantage of JPEG2000 over normal JPEG is that the error from JPEG2000 compression is smaller than the error from JPEG. Moreover, comparison of an image quality, a general evaluation tool, RMSE (Root Mean Square Error), has been adopted. The RMSE can be written by following. The results of functional testing of the constructed DICOM viewer showed that the program can open and display medical image and it s information with no distortion when compared with the original image and the program can process medical images with local contrast enhancement, interpolators techniques and cine loop. The Web-based Integrated Medical Information System for Telepathology by using Borland C++ Builder, PHP and MySQL for image archive, image compression, image processing and image transmission. For, the developed Endoscope camera has functional as shown in Figure 12. RMSE 1 MN M 1N 1 2 = { (, ) (. )} 2 f x y g x y x= 0 y = 0 1 (1) Table 1 and figure 11 shows the comparison results based on compression ratios with JPEG and JPEG2000. Which show that compressing image in JPEG2000 has less error than normal JPEG compression. Both compression processes will increase the number of errors when the compressing ratio has increased. Furthermore, the overall performance based on JPEG2000 shows better result than JPEG. TABLE 1 The RMSE Comparison JPEG and JPEG2000. Compression ratio 15:1 35:1 65:1 Compressing standard.jpg.jp2.jpg.jp2.jpg.jp2 Image Single Frame Multiframe Fig. 11 RMSE comparison curve. Fig. 12. The facilities in system a Web-based Integrated Medical Information System for Telepathology such as LoginPageGUI, StartProgramGUI, SettingDialog, HOTKEY, ProgramRunning, ImageCapture, NameDefine, ImageOpen, Information2Database, Main Home and Patientpage. Figure 13 depicts the architecture of our a Web-based Integrated Medical Information System for Telepathology. The DICOM server is connected to local/remote image acquisition system. Upon acquiring an image, the server stores the image in the DICOM v 3.0 format by using the DICOM encoding module. The stored image can be displayed by using the DICOM decoding module. The server also includes modules for image compression and DICOM viewer. Clients (a personal computer, a notebook or a PDA equipped with a Web browser) can download and install the DICOM viewer from the DICOM server via WWW. From then on, clients can be selected and opened single frame and 1143

6 multiframes, each of which can exhibit information in.dcm file format and digital image processing based on local contrast enhancement, adaptive interpolators techniques, colour transformation and cine loop. Also, for a situation in that a client wants to discuss with other client, the server provide facilities for making Webboard. ratio. And (3) our system can open single frame and multiframes, each of which can exhibit information in.dcm file format with no distortion and digital image processing based on local contrast enhancement, adaptive interpolators techniques, colour transformation and cine loop. The system has been developed and provided medical image services over long distance which showed the usefulness of our approach. ACKNOWLEDGMENT We would like to appreciate to all of instructors and friends at Department of Industrial Physics and Medical Instrumentation, Faculty of Applied Science, King Mongkut s University of Technology North Bangkok, Thailand. Figure 13. Basic structure and sequence of interactions between clients and server in a Web-based Integrated Medical Information System for Telepathology. Finally, The results of functional testing of the constructed a web-based DICOM-format image archive, medical image compression and DICOM viewer system for teleradiology application shows that a client can connect to the DICOM server through WWW, authentication by using a login processing is performed. The client can examine the list of image stored in DICOM server, select the desired image and download the selected image. When a client issues a command, then the command is transferred to DICOM server through the Web server. After, DICOM server finished the requested job, the result image is sent to the client through the Web server. In the event of image display and image processing is performed by DICOM viewer which the client can download the DICOM viewer in the form of plug-in from the server. CONCLUSION The Web-based Integrated Medical Information System for Telepathology provides the following facilities: (1) DICOMformat image archive. (2) Medical Image Compression based on JPEG and JPEG2000. and (3) DICOM viewer. The results shown that (1) our system can also convert the image data both single frame and multiframe in normal or automatic DICOM process into the standard DICOM 3.0 format without altering the image data. (2) The resulting images are then compressed with two different techniques JPEG and JPEG2000. The significant advantage of JPEG2000 over normal JPEG is that the error from JPEG2000 compression is smaller than the error from JPEG. Nevertheless, both methods share a similar mishap; when the compression ratio increases, they both generate more error than the processes on lower compression REFERENCES [1] Piyamas Suapang, Kobchai Dejhan and Surapun Yimmun, Medical Image Archiving, Processing, Analysis and Communication System for Teleradiology, Proceeding of TENCON 2010, Fukuoka International Congress Center, Fukuoka, Japan, November 21-24, [2] Kazuhiko HAMAMOTO, Study on Medical Ultrasonic Echo Image Compression by JPEG2000 Optimization and the subjective assessment of the quality, Proceeding of the IEEE, pp , October [3] NEMA PS 3, Digital Imaging nnd Communication in Medicine, 2004ed., Global Engineering Documents, Englewood CO, [4] Bas Revet, DICOM Cook Book for Implementations in Modalities, Nederland: Philips Medical Systems, [5] Chai, D.: Bouzerdoum. A.; JPEG2000 image compression: an overview, The Seventh Intelligent Information Systems Conference, Australian and New Zealand, pp , Nov I, [6] W. B. 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