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Pattern Recognition in Photoacoustic Dataset

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Abstract

In photoacoustic imaging, optical absorption properties of matter are imaged by detecting the ultrasound that is produced when the material is illuminated by a laser. For medical imaging, photoacoustics is a useful tool since matter in the human body has different optical absorption properties. In this study, pattern recognition systems are used to study a set of medical images for tumor identification and extraction—to detect the specific area in which the tumor is present. The objective is to incorporate this information into real-time image acquisition systems to improve medical diagnosis. Preliminary results obtained by studying the image dataset demonstrated the interchangeability of the proposed system. A system of automatic classification was constructed, using a set of images with and without cancerous tumors to evaluate the proposed method. The training set used was manually labeled, and the test set was never seen by the training set. The results helped us determine the feasibility of the proposed system.

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Authors and Affiliations

  1. División de Ingenierías del campus Irapuato—Salamanca, Carretera Salamanca—Valle de Santiago km 3.5+1.8 km Comunidad de Palo Blanco, 36885 , Salamanca, GTO, México

    R. Guzmán-Cabrera, M. Torres-Cisneros, J. Ruiz-Pinales, O. G. Ibarra-Manzano & G. Aviña-Cervantes

  2. Unidad Académica Multidisciplinaria Reynosa—Rodhe, Universidad Autónoma de Tamaulipas, Carretera Reynosa—San Fernando cruce con canal Rodhe, Colonia Arco iris, 88779 , Reynosa, TAMPS, México

    J. R. Guzmán-Sepúlveda & D. A. May-Arrioja

Authors
  1. R. Guzmán-Cabrera
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  2. J. R. Guzmán-Sepúlveda
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  3. M. Torres-Cisneros
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  4. D. A. May-Arrioja
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  5. J. Ruiz-Pinales
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  6. O. G. Ibarra-Manzano
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  7. G. Aviña-Cervantes
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Correspondence to R. Guzmán-Cabrera.

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Guzmán-Cabrera, R., Guzmán-Sepúlveda, J.R., Torres-Cisneros, M. et al. Pattern Recognition in Photoacoustic Dataset. Int J Thermophys 34, 1638–1645 (2013). https://doi.org/10.1007/s10765-013-1452-9

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  • DOI: https://doi.org/10.1007/s10765-013-1452-9

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