literature.bib

@article{sigproc:alasaarela_evaluation_1990,
	title = {Evaluation of image quality of ultrasound scanners in medical diagnostics},
	volume = {9},
	issn = {0278-4297},
	abstract = {The evaluation of the properties of ultrasound diagnostic scanners has not yet been standardized. Because the image itself is the basis of diagnostic decisions, it should also be the basis of evaluation of the capabilities of scanners. This study is aimed to help the standardization work by suggesting a procedure for testing the image quality of the scanners. The image quality depends on the tissue resolution, which is difficult to determine without real tissue studies. Therefore, the presented testing procedure consists of two parts: first, lateral and longitudinal resolution, image uniformity, sensitivity, and cyst and tumor imaging are determined by phantom tests; second, imaging experiments of formalin-fixed tissue samples are used to give information on the imaging capability of selected tissue details and boundaries. The procedure has been carried out by an experimental comparative test of 30 scanner and transducer combinations. The role of real tissue tests is important. A reliable whole-body phantom, including liquids flowing in veins, would be a breakthrough in testing real-time image quality.},
	language = {eng},
	number = {1},
	journal = {Journal of Ultrasound in Medicine: Official Journal of the American Institute of Ultrasound in Medicine},
	author = {Alasaarela, E. and Koivukangas, J.},
	month = jan,
	year = {1990},
	pmid = {2404131},
	keywords = {Brain, Equipment Design, Evaluation Studies as Topic, Humans, Image Enhancement, Kidney, Liver, Models, Structural, Ultrasonics, Ultrasonography},
	pages = {23--34}
}

@inproceedings{sigproc:rangaraju_review_2012,
	title = {Review Paper on Quantitative Image Quality Assessment Medical Ultrasound Images},
	volume = {Vol.1 - Issue 4 (June- 2012)},
	url = {http://www.ijert.org/view-pdf/187/review-paper-on-quantitative-image-quality-assessment--medical-ultrasound-images},
	abstract = {Review Paper on Quantitative Image Quality Assessment � Medical Ultrasound Images written by Kashyap Swathi Rangaraju, Dr. Kishor Kumar, C H Renumadhavi download},
	language = {English},
	urldate = {2017-05-06},
	publisher = {IJERT},
	author = {Rangaraju, Kashyap Swathi and Kumar, Dr Kishor and Renumadhavi, C. H.},
	month = jun,
	year = {2012},
	file = {Snapshot:/home/francis/.mozilla/firefox/vbm5ume3.Default User/zotero/storage/4TUVBJTW/review-paper-on-quantitative-image-quality-assessment--medical-ultrasound-images.html:text/html}
}

@article{sigproc:joy_automated_2014,
	title = {Automated performance assessment of ultrasound systems using a dynamic phantom},
	volume = {22},
	issn = {1742-271X},
	url = {http://dx.doi.org/10.1177/1742271X14549591},
	doi = {10.1177/1742271X14549591},
	abstract = {Quality assurance of medical ultrasound imaging systems is limited by repeatability, difficulty in quantifying results, and the time involved. A particularly interesting approach is demonstrated in the Edinburgh pipe phantom which, with an accompanying mathematical transformation, produces a single figure of merit for image quality from individual measurements of resolution over a range of depths. However, the Edinburgh pipe phantom still requires time-consuming manual scanning, mitigating against its routine use. This paper presents a means to overcome this limitation with a new device, termed the Dundee dynamic phantom, allowing rapid set-up and automated operation. The Dundee dynamic phantom is based on imaging two filamentary targets, positioned by computer control at different depths in a tank of 9.4\% ethanol–water solution. The images are analysed in real time to assess if the targets are resolved, with individual measurements at different depths again used to calculate a single figure of merit, in this case for lateral resolution only. Test results are presented for a total of 18 scanners in clinical use for different applications. As a qualitative indication of viability, the figure of merit produced by the Dundee dynamic phantom is shown to differentiate between scanners operating at different frequencies and between a relatively new, higher quality system and an older, lower quality system.},
	language = {en},
	number = {4},
	urldate = {2017-05-06},
	journal = {Ultrasound},
	author = {Joy, J and Riedel, F and Valente, AA and Cochran, S and Corner, GA},
	month = nov,
	year = {2014},
	pages = {199--204}
}

@incollection{sigproc:gupta_image_2016,
	series = {Studies in Computational Intelligence},
	title = {Image Quality Assessment: A Case Study on Ultrasound Images of Supraspinatus Tendon},
	copyright = {©2016 Springer International Publishing Switzerland},
	isbn = {978-3-319-33791-3 978-3-319-33793-7},
	shorttitle = {Image {Quality} {Assessment}},
	url = {http://link.springer.com/chapter/10.1007/978-3-319-33793-7_12},
	abstract = {With the advancement of technologies on visual contents and the rate at which data is being captured, viewed, stored, and shared, the importance of assessment of quality of the contents has major importance. Image quality assessment has remained a topic of research over the last several decades for optical as well as medical images. User oriented image quality assessment is playing a key role in the assessment of visual contents. Studies are conducted to imitate the accuracy of human visual system for assessment of images. This chapter details about the approaches for development of methods for image quality assessment followed by brief introduction on existing image quality assessment methods. Later in the chapter, challenges for validation and development of image quality assessment metric for medical images are briefly discussed followed by the case study for assessment of ultrasound images of supraspinatus tendon.},
	language = {en},
	number = {651},
	urldate = {2017-05-06},
	booktitle = {Medical {Imaging} in {Clinical} {Applications}},
	publisher = {Springer International Publishing},
	author = {Gupta, Rishu and Elamvazuthi, I. and George, J.},
	editor = {Dey, Nilanjan and Bhateja, Vikrant and Hassanien, Aboul Ella},
	year = {2016},
	note = {DOI: 10.1007/978-3-319-33793-7\_12},
	keywords = {Artificial Intelligence (incl. Robotics), Biomedical Engineering, Computational Intelligence, Imaging / Radiology, Signal, Image and Speech Processing},
	pages = {257--284}
}

@article{sigproc:venkatnarayanarao_assessment_2013,
	title = {Assessment of Diverse Quality Metrics for Medical Images Including Mammography},
	volume = {83},
	url = {http://adsabs.harvard.edu/abs/2013IJCA...83d..42V},
	doi = {10.5120/14440-2593},
	abstract = {Not Available},
	urldate = {2017-05-06},
	journal = {International Journal of Computer Applications},
	author = {VenkatNarayanaRao, T. and Govardhan, A.},
	month = dec,
	year = {2013},
	pages = {42--47}
}


@article{sigproc:ibrahim_assessment_2015,
	title = {Assessment of Image Quality vs. Computation Cost for Different Parameterizations of Ultrasound Imaging Pipelines},
	url = {https://infoscience.epfl.ch/record/209034?ln=fr},
	urldate = {2017-05-06},
	journal = {Proceedings of the 6th Workshop on Medical Cyber-Physical Systems},
	author = {Ibrahim, Aya and Simalatsar, Alena and Skalistis, Stefanos and Angiolini, Federico and Arditi, Marcel and Thiran, Jean-Philippe and De Micheli, Giovanni},
	year = {2015},
}

@inproceedings{sigproc:hemmsen_ultrasound_2010,
	title = {Ultrasound image quality assessment: a framework for evaluation of clinical image quality},
	shorttitle = {Ultrasound image quality assessment},
	url = {http://proceedings.spiedigitallibrary.org/proceeding.aspx?doi=10.1117/12.840664},
	doi = {10.1117/12.840664},
	urldate = {2017-05-06},
	author = {Hemmsen, Martin Christian and Petersen, Mads Møller and Nikolov, Svetoslav Ivanov and Nielsen, Michael Backmann and Jensen, Jørgen Arendt},
	editor = {D'hooge, Jan and McAleavey, Stephen A.},
	month = mar,
	year = {2010},
	pages = {76290C}
}