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Estimating quantitative physiological and morphological tissue parameters of murine tumor models using hyperspectral imaging and optical profilometry
Tadej Tomanič, Luka Rogelj, Jošt Stergar, Boštjan Markelc, Tim Božič, Simona Kranjc Brezar, Gregor Serša, Matija Milanič, 2022, izvirni znanstveni članek

Povzetek: Understanding tumors and their micro-environment are essential for successfuland accurate disease diagnosis. Tissuephysiology and morphology are altered intumors compared to healthy tissues, andthere is a need to monitor tumors and their surrounding tissues, includingblood vessels, non-invasively. This preliminary study utilizes a multimodaloptical imaging system combining hyperspectral imaging (HSI) and three-dimensional (3D) optical profilometry (OP) to capture hyperspectral imagesand surface shapes of subcutaneously grown murine tumor models. Hyper-spectral images are corrected with 3D OP data and analyzed using the inverse-adding doubling (IAD) method to extract tissue properties such as melaninvolume fraction and oxygenation. Blood vessels are segmented using theB-COSFIRE algorithm from oxygenation maps. From 3D OP data, tumor vol-umes are calculated and compared to manual measurements using a verniercaliper. Results show that tumors can be distinguished from healthy tissuebased on most extracted tissue parameters (p<0:05). Furthermore, blood oxy-genation is 50% higher within the blood vessels than in the surrounding tissue,and tumor volumes calculated using 3D OP agree within 26% with manualmeasurements using a vernier caliper. Results suggest that combining HSI andOP could provide relevant quantitative information about tumors and improvethe disease diagnosis.
Ključne besede: medical physics, hyperspectral imaging, diffuse reflectance spectroscopy, blood vessels, tumors
Objavljeno v DiRROS: 08.09.2022; Ogledov: 280; Prenosov: 100
.pdf Celotno besedilo (3,79 MB)

Discrimination between abiotic and biotic drought stress in tomatoes using hyperspectral imaging
Nik Susič, Uroš Žibrat, Saša Širca, Polona Strajnar, Jaka Razinger, Matej Knapič, Andrej Vončina, Gregor Urek, Barbara Gerič Stare, izvirni znanstveni članek

Povzetek: Crop plants are subjected to various biotic and abiotic stresses. Both root-knot nematodes (biotic stress) and water deficiency (abiotic stress) lead to similar drought symptoms in the plant canopy. In this work, hyperspectral imaging was used for early detection of nematode infestation and water deficiency (drought) stress in tomato plants. Hyperspectral data in the range from 400 to 2500 nm of plants subjected to different watering regimes and nematode infestation levels were analysed by partial least squares – discriminant analysis (PLS-DA) and partial least squares – support vector machine (PLS-SVM) classification. PLS-SVM classification achieved up to 100% accuracy differentiating between well-watered and water-deficient plants, and between 90 and 100% when identifying nematode-infested plants. Grouping the data according to the time of imaging increased the accuracy of classification. Shortwave infrared spectral regions associated with the OH and CH stretches were most relevant for the identification of nematode infested plants and severity of infestation. This study demonstrates the capability of hyperspectral imaging to identify and discriminate between biotic and abiotic plant stresses.
Ključne besede: nematode, Hyperspectral imaging, Drought stress, Root-knot nematode, Tomato
Objavljeno v DiRROS: 20.07.2018; Ogledov: 3407; Prenosov: 2026
.pdf Celotno besedilo (847,87 KB)
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