Diagnostically lossless compression of X-ray angiography images based on automatic segmentation using ray-casting and &amp;#x03B1;-shapes

Xu, Zhibin; Bartrina-Rapesta, Joan; Sánchez, Vı́ctor; Serra-Sagristà, Joan; Munoz-Gomez, Juan

doi:10.1109/icip.2013.6738152

Cited by 4 publications

(4 citation statements)

References 18 publications

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“…Specifically, we first remove the nonclinically relevant areas using a low-complexity segmentation method based on ray-casting and α-shapes [10]. The main difference with [10] is that the current manuscript explains with high detail all the parameters used in our proposal and justifies better the need for our approach, for instance presenting more segmentation results produced by more recent segmentation methods that do not work either. Further, the lossless compression performance is evaluated extensively using all coding techniques included in DICOM such as JPEG-LS, JPEG2000 and H.264 [12].…”

Section: Introductionmentioning

confidence: 99%

“…Diagnostically lossless coding, on the other hand, guarantees the perfect reconstruction of only those Regions of Interest (ROIs) that are used for diagnostic purposes. This is usually achieved by identifying the ROIs and applying lossless coding to only these regions and lossy coding to the background (BG) [7,8,9,10].…”

Section: Introductionmentioning

confidence: 99%

“…Recent published contributions are normally devised to a specific coding technique or to a particular compression strategy for angiography image. Depending on the compression strategy, contributions can be classified into lossy [11], lossless [6], or diagnostically lossless compression [8,10].…”

Section: Introductionmentioning

confidence: 99%

“…With regard to the recent diagnostically lossless coding methods developed for various medical images [7,8,9,10], most of them rely on segmentation to identify the ROI. Although these methods achieve competitive coding performances, they present two important drawbacks when applied to X-ray angio images.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Diagnostically lossless coding of X-ray angiography images based on background suppression

Bartrina-Rapesta

Blanes

et al. 2016

Computers & Electrical Engineering

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X-ray angiography images are widely used to identify irregularities in the vascular system. Because of their high spatial resolution and the large amount of images generated daily, coding of X-ray angiography images is becoming essential. This paper proposes a diagnostically lossless coding method based on automatic segmentation of the focal area using ray-casting and α-shapes. The diagnostically relevant Region of Interest is first identified by exploiting the inherent symmetrical features of the image. The background is then suppressed and the resulting images are encoded using lossless and progressive lossy-to-lossless methods, including JPEG-LS, JPEG2000, H.264 and HEVC. Experiments on a large set of X-ray angiography images suggest that our method correctly identifies the Region of Interest. When compared to the case of coding with no background suppression, the method achieves average bit-stream reductions of nearly 34% and improvements on the reconstruction quality of up to 20 dB-SNR for progressive decoding.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Diagnostically lossless coding of X-ray angiography images based on background suppression

Bartrina-Rapesta

Blanes

et al. 2016

Computers & Electrical Engineering

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Region of interest extraction for lossless compression of bone X-ray images

Kazeminia

Karimi

Soroushmehr

et al. 2015

2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

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For few decades digital X-ray imaging has been one of the most important tools for medical diagnosis. With the advent of distance medicine and the use of big data in this respect, the need for efficient storage and online transmission of these images is becoming an essential feature. Limited storage space and limited transmission bandwidth are the main challenges. Efficient image compression methods are lossy while the information of medical images should be preserved with no change. Hence, lossless compression methods are necessary for this purpose. In this paper, a novel method has been proposed to eliminate the non-ROI data from bone X-ray images. Background pixels do not contain any valuable medical information. The proposed method is based on the histogram dispersion method. ROI is separated from the background and it is compressed with a lossless compression method to preserve medical information of the image. Compression ratios of the implemented results show that the proposed algorithm is capable of effective reduction of the statistical and spatial redundancies.

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Lossless Compression of Angiogram Foreground with Visual Quality Preservation of Background

Ahmadi

Emami

Hajabdollahi

et al. 2018

2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

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Diagnostically lossless compression of X-ray angiography images based on automatic segmentation using ray-casting and α-shapes

Cited by 4 publications

References 18 publications

Diagnostically lossless coding of X-ray angiography images based on background suppression

Diagnostically lossless coding of X-ray angiography images based on background suppression

Region of interest extraction for lossless compression of bone X-ray images

Lossless Compression of Angiogram Foreground with Visual Quality Preservation of Background

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