scholarly journals An Medical Image File Formats and Digital Image Conversion

Medical image file formats make the confusing aspect to young researchers who start work with medical images. Medical image format conversion is still a tedious task due to the different structure of files. Digital image conversion from the medical image is an important pre-processing step to the process and visualizes the data. This article presents an overview of the major medical image file formats such as Analyze, neuro-imaging informatics technology initiative (NIFTI), MINC, and digital imaging and communications in medicine (DICOM). Then the characteristics and strengths of the various formats are discussed. Also the article describes the easiest way of digital image conversion from medical image format.

2003 ◽  
Author(s):  
Scott C. Neu ◽  
Daniel J. Valentino ◽  
Keith R. Ouellette ◽  
Arthur W. Toga

2020 ◽  
Vol 26 (S2) ◽  
pp. 1176-1178
Author(s):  
Grigore Moldovan ◽  
Michael Zabel

AbstractExperimental data, simulation, data analysis and visualisation require image file formats that are open source and able to contain and manage quantitative data. Quantification techniques bring the new challenge of managing image calibration parameters and formulas in an open and efficient format, compatible with routine microscopy workflows. A practical approach to quantitative image format is presented and discussed here, relying on open and extensible file formats - Tagged Image File (TIF) and Extensible Metadata Platform (XMP).


2013 ◽  
Vol 27 (2) ◽  
pp. 200-206 ◽  
Author(s):  
Michele Larobina ◽  
Loredana Murino

Different image formats are available in the world today which are used for various purposes, this paper elaborates the Ontology of different Image File Formats and their various applications. Digital images are saved in various Image File Formats which have different properties and features which are ideal for a particular use. A digital image is primarily classified into two types, raster or vector type. Image format elucidate how the information in the image will be stored. Image file format is a systematic way of storing and arranging digital images. Image file format can store data in compressed format (which may be lossy or lossless), uncompressed format or a vector format. Some Image format are suitable for a particular purpose while some are not. TIFF Image type is good for printing whereas PNG or JPG, are best for web. Analysis of the basic Image File Format have been carried out practically and the result is displayed in the coming section


Author(s):  
Sophie Triantaphillidou ◽  
Elizabeth Allen

2011 ◽  
pp. 315-328
Author(s):  
Sophie Triantaphillidou ◽  
Elizabeth Allen

2011 ◽  
Vol 2 (1) ◽  
Author(s):  
Vina Chovan Epifania ◽  
Eko Sediyono

Abstract. Image File Searching Based on Color Domination. One characteristic of an image that can be used in image searching process is the composition of the colors. Color is a trait that is easily seen by man in the picture. The use of color as a searching parameter can provide a solution in an easier searching for images stored in computer memory. Color images have RGB values that can be computed and converted into HSL color space model. Use of HSL images model is very easy because it can be calculated using a percent, so that in each pixel of the image can be grouped and named, this can give a dominant values of the colors contained in one image. By obtaining these values, the image search can be done quickly just by using these values to a retrieval system image file. This article discusses the use of the HSL color space model to facilitate the searching for a digital image in the digital image data warehouse. From the test results of the application form, a searching is faster by using the colors specified by the user. Obstacles encountered were still searching with a choice of 15 basic colors available, with a limit of 33% dominance of the color image search was not found. This is due to the dominant color in each image has the most dominant value below 33%.   Keywords: RGB, HSL, image searching Abstrak. Salah satu ciri gambar yang dapat dipergunakan dalam proses pencarian gambar adalah komposisi warna. Warna adalah ciri yang mudah dilihat oleh manusia dalam citra gambar. Penggunaan warna sebagai parameter pencarian dapat memberikan solusi dalam memudahkan pencarian gambar yang tersimpan dalam memori komputer. Warna gambar memiliki nilai RGB yang dapat dihitung dan dikonversi ke dalam model HSL color space. Penggunaan model gambar HSL sangat mudah karena dapat dihitung dengan menggunakan persen, sehingga dalam setiap piksel gambar dapat dikelompokan dan diberi nama, hal ini dapat memberikan suatu nilai dominan dari warna yang terdapat dalam satu gambar. Dengan diperolehnya nilai tersebut, pencarian gambar dapat dilakukan dengan cepat hanya dengan menggunakan nilai tersebut pada sistem pencarian file gambar. Artikel ini membahas tentang penggunaan model HSL color space untuk mempermudah pencarian suatu gambar digital didalam gudang data gambar digital. Dari hasil uji aplikasi yang sudah dibuat, diperoleh pencarian yang lebih cepat dengan menggunakan pilihan warna yang ditentukan sendiri oleh pengguna. Kendala yang masih dijumpai adalah pencarian dengan pilihan 15 warna dasar yang tersedia, dengan batas dominasi warna 33% tidak ditemukan gambar yang dicari. Hal ini disebabkan warna dominan disetiap gambar kebanyakan memiliki nilai dominan di bawah 33%. Kata Kunci: RGB, HSL, pencarian gambar


2006 ◽  
Vol 15 (01) ◽  
pp. 70-73
Author(s):  
R.W Westphal ◽  

SummaryObjectives:To summarize current excellent research in the field of sensor, signal and imaging informatics.Method:Synopsis of the articles selected for the IMIA Yearbook 2007.Results:The selection process for this yearbook section “Sensor, signal and imaging informatics” results in five excellent articles, representing research in four different nations. Papers from the fields of brain machine interfaces, sound surveillance in telemonitoring, soft tissue modeling, and body sensors have been selected.Conclusion:The selection for this yearbook section can only reflect a small portion of the worldwide copious work in the field of sensors, signal and image processing with applications in medical informatics. However, the selected papers demonstrate, how advances in this field may positively affect future patient care.


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