XSITRAY: A Database for the Detection of Osteoporosis Condition.
In Later stage of X-ray, expansion in the field of quantity of bone density was the recognition of single-photon absorptiometry (SPA) by Cameron and Sorenson in the year 1963. In terms of amount of BMD, SPA showed a superior place, but limited its use in the site of the measurement. In the recent development, struggling in the Dual energy is betrothed in Dual-photon absorptiometry (DPA), helping the synchronized transmission of gamma rays with the energies of the photon (1). The bone and bone tissue densities are measured by the Algebraic derivations. In late 1980s, grander and luxurious radioactive sources have been outdated by the use of single x-ray absorptiometry (SXA) and Dual Energy X-ray absorptiometry (DEXA). Compared to other predictable scanning, the success rate of SXA and DXA is also very high used for measurement of bone content (2). The main principle in the BMD measurement is to assist the physicians to perceive osteoporosis and envisage the danger of bone rupture. Thus osteoporosis affects the various regions of the skeleton with dissimilar cruelty. Most women are affected by the osteoporosis.
The key complexity of osteoporosis is rupture happening after tiniest trauma. Hip fractures are linked with enlarged short term mortality and high morbidity. The major regions such as Hip, vertebral, and radius fractures escalate the risk of upcoming break in various bones (3). Thus it is an obligatory step for investigators in biomedical domain, to yield suitable preclusion methods or efficient treatment processes for the patients. A bone mineral density (BMD) test processes the prediction of calcium and other kinds of minerals are in the part of the bone (4). Based on above said literature, in this proposed work we developed a database of X-Ray images which we baptized it as 'XSITRAY Database', for the profit of biomedical engineering research people. Even though a lot of medical databases are available for various imaging modalities, the significant pitfall in the bone research and development is that, unapproachability of suitable bone medical databases. Even though some survey has discussed the issues of various scan methods, they didn't offer any such databases publically accessible for the researchers.
Thus interested by the above said factors, our main offerings are:
* Generate a novel XSITRAY database, which comprises of 78 Spine, Femur, Clavicle, Extremity & Ankle, Extremity & Hand and Knee bones X-Ray scan images.
* Interprets all the subject's Gender, age and the position.
In the medical era, still now there is no exact database in bone images for further research and development. Motivated by all these factors, we created a new and exceptional database, XSITRAY database. This database is mainly focused for the BMD measurements.
X-ray bone images are retrieved from a research foundation centre. This dataset involves of 78 X-Ray scan images collected from various subjects. XSITRAY consist of 52 female and 26 male subjects. Each subject includes Spine, Femur, Clavicle, Extremity & Ankle, Extremity & Hand and Knee bones X-Ray scan images. The sample spine scan images of 5 subjects are shown in Figure.1. Similarly, the samples X-ray femur images of 5 subjects are shown in Figure.2. Table 1 and Table 2 describes the details of the subjects. The sample X-Ray clavicle scan images of 5 subjects are shown in Figure.3. The XSITRAY database is deliberated through subsequent stages:
1) Structure Details
2) Marking the XSITRAY images
These are explained step by step.
The standard database is created from the Indian X-ray images. In the 78 subjects, there are totally 9 Spine, 12 Femur, 28 Clavicle, 6 Extremity & Ankle, 12 Extremity & Hand and 11 Knee bones X-Ray scan images.
The images are harvested physically and hoarded as discrete images in 'png' (portable network graphics) format. The detailed information about the X Ray scan images of all the subjects, have also been delivered in the table format. The entire dataset is grouped as six groups such as XSITRAY-SP, XSITRAY-FE, XSITRAY-CL, XSITRAY-EA, XSITRAY-EH and XSITRAY-KN. The XSITRAY-SP includes the X-Ray images of 9 spine bone images. Similarly XSITRAY-FE, XSITRAY-CL, XSITRAY-EA, XSITRAY-EH and XSITRAY-KN consists of 12 Femur, 28 Clavicle, 6 Extremity & Ankle, 12 Extremity & Hand and 11 Knee bone images. The labeling of the database, encourage the investigators to understand and scrutinize the scores of the spine, femur, clavicle, Extremity &Ankle, Extremity & Hand and Knee bones separately.
Marking the XSITRAY Images
The proposed databases are labeled flawlessly for the easy understanding of researchers. The annotation involves the identification of the subject ID, part of the bone and gender. Consider an example, the marker for a X Ray image is given as: XRAY_SP_001.png. Here, in the initial, X-Ray refers to X-Ray scan image, SP interprets to the spine image of subject and 001 is the ID of the subject. Likewise XRAY_FE_002.png mentions to X-Ray femur image of a subject with a subject ID of 002. Likewise XRAY_CL_002.png denotes to X-Ray clavicle image of a subject with a subject ID of 002, XRAY_EA_002.png states to X-Ray Extremity & Ankle image of a subject with a subject ID of 002, XRAY_EH_002.png denotes to X-Ray Extremity & Hand image of a subject with a subject ID of 002 and XRAY_KN_002 raises to X-Ray knee image of a subject with a subject ID of 002.
XSITRAY affords a complete labelling through a careful investigation of all X-Ray scan images. All the images are annotated manually with the following labels for each bone image.
* Specific ID
* Age and
* Type of Image
* View (Anterior/Posterior)
The database creation is through the motivation by the lot of problems associated to orthopedic applications. All the medical report values for the spine, Ankle, clavicle, femur and Knee bone images are presented which might be convenient in the development of bone research. Fig. 3 displays the sample labelling of a subject from the dataset.
Clinical Data Analysis
Osteoporosis, a disease usually connected with humans, is categorized by diminish in mass of the bone and micro architectural integrity (5). One critical problem in the growth of osteoporosis is the achievement of apposite peak mass in childhood and later stages (6). A disappointment in the attainment of youth peak bone mass may be related with premature osteoporosis and augmented fracture risk (7). World Health Organization (WHO) defines T-Score values for human beings in BMD plot as -1 SD for normal, -1 and -2.5 for Osteopenia, below -2.5 SD for Osteoporosis
Table 1, Table 2 and Table 3 show the medical report of the same persons.
Based on the BMD levels, T-score and Z-score, mild to destructive therapies are needed in the form of Hormone replacement therapy (HRT), Bisphosphonates, Calcitonin and SERMs as suggested by the orthopedician. Moreover, all patients should confirm an tolerable intake of dietary calcium (1200 mg/d) and vitamin D (400800 IU daily). By exact study of the X-Ray bone images and their reports, people can be prevented from the osteoporosis disease.
Based on the database medical reports provided by the physician/experts, the biomedical investigators can validate their accuracy of biomedical algorithms.
The projected paper presented a medical image datasets called XSITRAY, a group of X-ray scan images for healthcare and orthopedic research. It is established with the meaning of supplementing a standard for bone research and related development. The foremost features of this XSITRAY database are:
a) spine X Ray images, femur, clavicle, Extremity and Ankle, Extremity and Hand and knee, X Ray images each. b) Labeling the subject's biological data. By creating and making this database available to the research in BME community, we optimizes to promote the investigation of many indeterminate problems. XSITRAY database along with all medical measures will be made accessible for investigation purposes. The XSITRAY database can be observed and downloaded at the institutional web address: http://www.sethu.ac.in/ XSITRAY/.
(Received: 29 November 2018; accepted: 09 March 2019)
(1.) Bonnick, S.L, "Bone Densitometry for Technologists" Thesis Report: Springer, pp1-64, 2006.
(2.) S.M. Nazia Fathima, R. tamilselvi and M. Parisa Beham, "Role of Dual-Energy X-ray Absorptiometry in Assessment of Bone Mineral Density--A Review" Proceedings of International Conference on Informatics Computing in Engineering Systems ICICES, (2018).
(3.) Rosa Lorente-Ramos Javier Azpeitia-Arman Araceli Munoz-Hernandez Jose Manuel arciaGomez Patricia Diez-Martinez Miguel rande-Barez Dual-Energy X-Ray absorptiometry in the Diagnosis of Osteoporosis: A Practical Guide, AJR; 196: 897-904 0361-803X/11/1964-897, 2011.
(4.) M. K. Garg and Sandeep Kharb,"Dual energy X-ray absorptiometry: Pitfalls in measurement and interpretation of bone mineral density" Indian Journal of Endrocrinology and metabolism, (2013).
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(6.) Rabinovich CE. "Bone mineral status in juvenile rheumatoid arthritis", J Rheumatol Suppl, 58: 34-7 (2000).
(7.) S C Lacassagne, P N. Tyrrell, E Atenafu, A S. Doria, D Stephens, D Gilday, and E D. Silverman "Prevalence and Etiology of Low Bone Mineral Density in Juvenile Systemic Lupus Erythematosus", Arthritis & Rheumatism, 56(6): pp 1966-1973 (2007).
(8.) R.M. Lorente Ramos, J. Azpeitia Arman, N. Arevalo Galeano, A. Munoz Hernandez, J.M. Garcia Gomez, J. Gredilla Molinero "Dual energy X-ray absorptimetry: Fundamentals, methodology, and clinical applications" Radiologia.; 54(5):410-423 (2012).
S.M. Nazia Fathima # , R. Tamilselvi *  and M. Parisa Beham  *
# Department of CSE, * Department of ECE, #* Sethu Institute of Technology, Tamilnadu-626 115, India.
* Corresponding author E-mail: firstname.lastname@example.org
Caption: Fig. 1. X-Ray scan images of spine of 5 selected subjects from the XSITRAY
Caption: Fig. 2. Sample X-Ray Femur images of 5 subjects
Caption: Fig. 3. Labelling of spine, femur and clavicle bone images
Caption: Fig. 4. Sample images from XSITRAY database: From top to bottom (a) hand (b) Hand and extremity (c) Knee and extremity (d) Clavicle and (e) Ankle and extremity
Table 1. Interpretation of Spine X-Ray images Subject Id Gender Age Image XRAY SP 001 F 37 Spine XRAY SP 002 F 70 Spine XRAY SP 003 F 58 Spine XRAY SP 004 F 65 Spine XRAY SP 005 F 69 Spine Table 2. Interpretation of femur X-Ray images Subject Id Gender Age Image XRAY FE 001 F 37 Femur XRAY FE 003 F 70 Femur XRAY FE 006 F 58 Femur XRAY FE 009 F 65 Femur XRAY FE 010 F 69 Femur Table 3. Interpretation of Clavicle X- Ray images Subject Id Gender Age Image XRAY CL 001 F 29 Clavicle XRAY CL 002 F 74 Clavicle XRAY CL 003 F 60 Clavicle XRAY CL 004 F 84 Clavicle XRAY CL 005 F 52 Clavicle
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|Author:||Fathima, S.M. Nazia; Tamilselvi, R.; Beham, M. Parisa|
|Publication:||Biomedical and Pharmacology Journal|
|Date:||Mar 1, 2019|
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