Int J Health Geogr - Hyperspectral hybrid method classification for detecting altered mucosa of the human larynx.

Tópicos

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Resumo

CKGROUND: In the field of earth observation, hyperspectral detector systems allow precise target detections of surface components from remote sensing platforms. This enables specific land covers to be identified without the need to physically travel to the areas examined. In the medical field, efforts are underway to develop optical technologies that detect altering tissue surfaces without the necessity to perform an excisional biopsy. With the establishment of expedient classification procedures, hyperspectral imaging may provide a non-invasive diagnostic method that allows determination of pathological tissue with high reliability. In this study, we examined the performance of a hyperspectral hybrid method classification for the automatic detection of altered mucosa of the human larynx.MATERIALS AND METHODS: Hyperspectral Imaging was performed in vivo and 30 bands from 390 to 680 nm for 5 cases of laryngeal disorders (2x hemorrhagic polyp, 3x leukoplakia) were obtained. Image stacks were processed with unsupervised clustering (linear spectral unmixing), spectral signatures were extracted from unlabeled cluster maps and subsequently applied as end-members for supervised classification (spectral angle mapper) of further medical cases with identical diagnosis.RESULTS: Linear spectral unmixing clearly highlighted altered mucosa as single spectral clusters in all cases. Matching classes were identified, and extracted spectral signatures could readily be applied for supervised classifications. Automatic target detection performed well, as the considered classes showed notable correspondence with pathological tissue locations.CONCLUSIONS: Using hyperspectral classification procedures derived from remote sensing applications for diagnostic purposes can create concrete benefits for the medical field. The approach shows that it would be rewarding to collect spectral signatures from histologically different lesions of laryngeal disorders in order to build up a spectral library and to prospectively allow non-invasive optical biopsies.

Resumo Limpo

ckground field earth observ hyperspectr detector system allow precis target detect surfac compon remot sens platform enabl specif land cover identifi without need physic travel area examin medic field effort underway develop optic technolog detect alter tissu surfac without necess perform excision biopsi establish expedi classif procedur hyperspectr imag may provid noninvas diagnost method allow determin patholog tissu high reliabl studi examin perform hyperspectr hybrid method classif automat detect alter mucosa human larynxmateri method hyperspectr imag perform vivo band nm case laryng disord x hemorrhag polyp x leukoplakia obtain imag stack process unsupervis cluster linear spectral unmix spectral signatur extract unlabel cluster map subsequ appli endmemb supervis classif spectral angl mapper medic case ident diagnosisresult linear spectral unmix clear highlight alter mucosa singl spectral cluster case match class identifi extract spectral signatur readili appli supervis classif automat target detect perform well consid class show notabl correspond patholog tissu locationsconclus use hyperspectr classif procedur deriv remot sens applic diagnost purpos can creat concret benefit medic field approach show reward collect spectral signatur histolog differ lesion laryng disord order build spectral librari prospect allow noninvas optic biopsi

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