Mono- and multimodal registration of optical breast images

Pearlman, Paul C.; Adams, Arthur L.L.; Elias, Sjoerd G.; Mali, Willem P.Th.M.; Viergever, Max A.; Pluim, Josien P. W.

doi:10.1117/1.jbo.17.8.080901

Cited by 13 publications

(7 citation statements)

References 109 publications

(132 reference statements)

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“…Their concentration and distribution mappings within tissue can be reconstructed by measuring the optic signals at multiple wavelengths. 94,95 These mappings may potentially help in differentiating malignant from benign lesions.…”

Section: Optical Imagingmentioning

confidence: 99%

Recent Advances and Application of Breast Imaging in Clinical Practice

Wl¹,

Sitt²,

Fung³

et al. 2015

Hong Kong J Radiol

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Breast imaging is an essential cornerstone in the management of breast cancer. It serves not only as breast cancer screening, but also in diagnosis, treatment, and follow-up of patients with breast disease. Attempts to enhance the current imaging modalities and development of new technology are underway. We provide a short overview of the existing imaging modalities including mammography, tomosynthesis, ultrasound and magnetic resonance imaging, and recent technological advances including positron emission mammography, contrast digital mammography, elastography, three-dimensional / contrast-enhanced ultrasound and automated wholebreast ultrasound screening. Magnetic resonance spectroscopy, new state-of-the-art applications in optical imaging, cone-beam computed tomography, magnetic resonance-ultrasound navigation, and molecular imaging techniques are also briefly discussed.

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Section: Optical Imagingmentioning

confidence: 99%

Recent Advances and Application of Breast Imaging in Clinical Practice

Wl¹,

Sitt²,

Fung³

et al. 2015

Hong Kong J Radiol

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“…OM has been widely studied for the characterization of breast tissue and the identification of breast lesions, thanks to its sensitivity to physiological parameters altered by the presence of unhealthy tissue and to the use of non-ionizing health-safe radiation in the visible light spectrum and Near-Infrared (NIR) light spectrum (from 630 nm to 1100 nm) [1,[4][5][6]. Further novel promising application fields are gaining interest in the scientific community, like the monitoring of neoadjuvant chemotherapy and prediction of its pathologic outcome, as well as the assessment of risk for breast cancer development [4,[6][7][8][9]. OM could thus contribute to optimizing screening/diagnostic paths as well as treatment design, increasing patients' survival rate and improving their quality of life.…”

Section: Introductionmentioning

confidence: 99%

High throughput detection chain for time domain optical mammography

Ferocino

Martinenghi

Mora

et al. 2018

Biomed. Opt. Express

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A novel detection chain, based on 8 Silicon Photomultipliers (forming a wide-area custom-made detection probe) and on a time-to-digital converter, was developed to improve the signal level in multi-wavelength (635-1060 nm) time domain optical mammography. The performances of individual components and of the overall chain were assessed using established protocols (BIP and MEDPHOT). The photon detection efficiency was improved by up to 3 orders of magnitude, and the maximum count rate level was increased by a factor of 10 when compared to the previous system, based on photomultiplier tubes and conventional time-correlated single-photon counting boards. In the estimate of optical parameters, the novel detection chain provides performances comparable to the previous system, widely validated in clinics, but with higher signal level, higher robustness, and at a lower price per channel, thus targeting important requirements for clinical applications.

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“…Holden has reviewed non-rigid geometric transformation models [19]. Other authors have drawn attention to specific anatomic regions, for example, cardiac image registration [20], or on techniques used for specific purposes, such as brain functional image localization [21], optical breast imaging [22], minimally invasive surgical procedures [23], and coronary heart disease [24]. Image registration in the computational intelligence framework has been reviewed by Ramirez et al [25], while others emphasize high-performance computing (HPC) [26], metaheuristics such as evolutionary algorithms [27], and implementations on the graphical processing units [28,29].…”

Section: Introductionmentioning

confidence: 99%

Survey of Non-Rigid Registration Tools in Medicine

2016

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We catalogue available software solutions for non-rigid image registration to support scientists in selecting suitable tools for specific medical registration purposes. Registration tools were identified using nonsystematic search in Pubmed, Web of Science, IEEE Xplore® Digital Library, Google Scholar, and through references in identified sources (n = 22). Exclusions are due to unavailability or inappropriateness. The remaining (n = 18) tools were classified by (i) access and technology, (ii) interfaces and application, (iii) living community, (iv) supported file formats, and (v) types of registration methodologies emphasizing the similarity measures implemented. Out of the 18 tools, (i) 12 are open source, 8 are released under a permissive free license, which imposes the least restrictions on the use and further development of the tool, 8 provide graphical processing unit (GPU) support; (ii) 7 are built on software platforms, 5 were developed for brain image registration; (iii) 6 are under active development but only 3 have had their last update in 2015 or 2016; (iv) 16 support the Analyze format, while 7 file formats can be read with only one of the tools; and (v) 6 provide multiple registration methods and 6 provide landmark-based registration methods. Based on open source, licensing, GPU support, active community, several file formats, algorithms, and similarity measures, the tools Elastics and Plastimatch are chosen for the platform ITK and without platform requirements, respectively. Researchers in medical image analysis already have a large choice of registration tools freely available. However, the most recently published algorithms may not be included in the tools, yet.

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Mono- and multimodal registration of optical breast images

Cited by 13 publications

References 109 publications

Recent Advances and Application of Breast Imaging in Clinical Practice

Recent Advances and Application of Breast Imaging in Clinical Practice

High throughput detection chain for time domain optical mammography

Survey of Non-Rigid Registration Tools in Medicine

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