title: Clustered targets imaged by optical tomography guided by ultrasound.
abstract: Clustered small breast lesions may be present in the neighboring areas and are difficult to accurately resolve and quantify in diffuse optical tomography. In addition, larger cancers are often accompanied by clustered satellite lesions in the neighboring areas, which are also difficult to resolve and quantify. To improve the light quantification of clustered lesions, a new multi-zone reconstruction algorithm guided by co-registered ultrasound (US) was investigated using simulations, phantoms, and clinical examples. This method separated one larger region-of-interest (ROI) into several ROIs based on the location information provided by co-registered US. In general, the single-ROI method cannot resolve two smaller targets when their separations were less than 2.5 cm and the depth was greater than 2.0 cm. The multi-zone reconstruction method improved the resolving ability and reconstruction accuracy. As a result, two targets located at 2.5 cm depth with separation greater than 2.0 cm could be distinguished, and reconstruction improved by more than 20% as compared with that of the single-ROI method. When two targets, one larger and one smaller, were located closer to each other, the location of the reconstructed absorption mass was shifted toward the larger target and the quantification of the smaller target was limited.
authors.affiliation: University of Connecticut, Electrical and Computer Engineering Department, Storrs, Connecticut 06269, USA.
authors.forename: Yan
authors.initials: Y
authors.lastname: Xu
authors.forename: Chen
authors.initials: C
authors.lastname: Xu
authors.forename: Quing
authors.initials: Q
authors.lastname: Zhu
mesh_terms: D000465:Algorithms; D001943:Breast Neoplasms / Q000175:diagnosis* / Q000000981:diagnostic imaging*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000706:statistics & numerical data; D019047:Phantoms, Imaging; D041622:Tomography, Optical / Q000379:methods* / Q000706:statistics & numerical data; D016217:Ultrasonography, Mammary / Q000379:methods* / Q000706:statistics & numerical data