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Hyperspectral Imaging to Discern Malignant and Benign Canine Mammary TumorsSahu, Amrita January 2013 (has links)
Hyperspectral imaging is an emerging technology in the field of biomedical engineering which may be used as a non-invasive modality to characterize tumors. In this thesis, a hyperspectral imaging system was used to characterize canine mammary tumors of unknown histopathology (pre-surgery) and correlate the results with the post-surgical histopathology results. The system consisted of a charge coupled device (CCD) camera, a liquid crystal tunable filter in the near infrared range (650-1100 nm), and a controller. Spectral signatures of malignant and benign canine mammary tumors were extracted and analyzed. The reflectance intensities of malignant tumor spectra were generally lower than benign tumor spectra over the wavelength range 650-1100nm. Previous studies have shown that cancerous tissues have a higher hemoglobin and water content, and lower lipid concentration with respect to benign tissues. The decreased reflectance intensity observed for malignant tumors is likely due to the increased microvasculature and, therefore, higher blood content of malignant tissue relative to benign tissue. Second derivative method was applied to the reflectance spectra. Peaks at 700, 840, 900 and 970 nm were observed in the second derivative reflectance spectra. These peaks were attributed to deoxy-hemoglobin, oxy-hemoglobin, lipid and water respectively. A Tissue Optical Index (TOI) was developed that enhances contrast between malignant and benign canine tumors. This index is based on the ratio of the reflectance intensity values corresponding to the wavelengths associated with the four chromophores. Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) were also applied on the canine spectral dataset and the method was cross-validated. Preliminary results from 22 canine mammary tumors showed that the sensitivity and specificity of the PCA-LDA is method is 86% and 86% respectively. The sensitivity and specificity of the TOI model is 86% and 95% respectively. These results show promise in the non-invasive optical diagnosis of canine mammary cancer. / Electrical and Computer Engineering
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INTERCHANGEABLE SMARTPHONE TACTILE IMAGING PROBE SYSTEM AND APPLICATIONSChoi, Sung In, 0000-0001-9255-7540 January 2023 (has links)
Many medical devices have been shifting to personal platforms such as smartphones due to its ubiquitous availability, variety of included sensors, robust communication, and user-friendliness. By utilizing smartphones as a medical sensing device should improve the early detection of abnormalities and the long-term monitoring of health conditions. Tissue abnormalities will be detected by touch sensation due to mechanical property changes within the tissue. However, touch sensation is unquantifiable and subjective. We integrate the smartphone with a tactile sensor to build a portable and personalized tissue assessment device based on changes in mechanical properties. The Smartphone Tactile Imaging Probe (STIP) is developed to quantify the mechanical properties of the tissue. The proposed system has a dual-sensing mode: compression-based sensing (STIP-C) and indentation-based sensing (STIP-I). STIP–C is designed to detect and measure the size and hardness of the inclusion. It assesses mechanical property changes caused by the tumor inside the tissue. STIP–I is designed to measure the pitting parameters and viscoelastic properties of the tissue. This system will assess the viscoelasticity changes caused by fluid retention within the tissue. STIP estimates mechanical and viscoelastic behavior changes in the tissue and provides the risk evaluation of an underlying health problem.
Breast cancer risk assessment and edema severity level classification are the main applications of STIP. We estimate the breast cancer risk by incorporating the patient’s personal risk value into the STIP-C data associated with the tumor mechanical properties to improve the risk assessment accuracy. To classify the edema severity level, the STIP-I measures the pitting parameters and viscoelastic properties of the tissue. From these parameters, we build a Viscoelastic Pitting Recovery (VPR) model. The model illustrates the changes in tissue viscoelastic behavior associated with the edema severity level. Using the VPR model, we use the thresholding method to classify the edema cases. We also developed customized phantoms representing the different amounts of fluid retention in the tissue. The experimental result found a relationship between the amounts of pitted depth from STIP-I and the fluid amount of a phantom.
In this dissertation, we developed and tested a portable tissue mechanical property estimation system. The interchangeable dual-mode STIP sensing probe and risk assessment methods were developed for the breast tumor malignancy and edema severity applications. / Electrical and Computer Engineering
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Charakterisierung von Lebertumoren nach kontrastverstärkter Sonographie und digitaler GraustufenbestimmungChopra, Sascha Santosh 19 January 2006 (has links)
Charakterisierung von Lebertumoren nach kontrastverstärkter Sonographie und digitaler Graustufenbestimmung Ziel: Die Charakterisierung fokaler Leberläsionen ist Bestandteil des klinischen Alltags und für Patienten von therapeutischer und prognostischer Relevanz. Auf diesem Gebiet wurde bisher die native Sonographie regulär eingesetzt. Eine sichere Artdiagnose bei unklaren Lebertumoren ist jedoch nur selten möglich. Die Einführung der kontrastmittelverstärkten Sonographie hat die differentialdiagnostischen Optionen erweitert. Ziel dieser Studie war es, den Nutzen des kontrastmittelverstärkten Ultraschalls und der anschließenden digitalen Graustufenanalyse bei fokalen Leberläsionen zu bewerten. Methodik: In einer prospektiven Studie wurde bei 50 Patienten mit CT oder MRT gesicherten Lebertumoren eine Sonographie des Oberbauches in nativer Sonographie und in Phaseninversionstechnik mit intravenöser Gabe des Ultraschallkontrastmittels SonoVue® durchgeführt. Nach Kontrastmittelgabe wurden über 120 s digitale Standbilder akquiriert. Mittels Software ermittelte man den dynamischen Graustufenverlauf für jeden einzelnen Tumor. Es folgte der Vergleich der einzelnen bildgebenden Modalitäten untereinander. Ergebnisse: Der Anteil der artdiagnostisch korrekten Zuordnungen belief sich in der CT bzw. MRT auf 78% und in der nativen Sonographie auf 60%. Mit Hilfe des kontrastmittelverstärkten Ultraschalls konnte er auf 86% gesteigert werden. Die digitale Graustufenanalyse lieferte für die einzelnen Tumorentitäten charakteristische Kurvenverläufe. Hierbei erwiesen sich die Zeitpunkte 20 s und 100 s nach Kontrastmittelgabe für die artspezifische Charakterisierung und für die Differenzierung in benigne und maligne Tumoren als optimal. Schlussfolgerung: Die kontrastmittelverstärkte Sonographie und deren digitale Graustufenbestimmung bilden eine Ergänzung der bisherigen Diagnostik von Lebertumoren und ermöglichen eine bessere Charakterisierung der Herde. Dies sollte in zusätzlichen Studien evaluiert werden. / Characterization of Hepatic Tumors with Contrast-enhanced Ultrasound and Digital Gray-Scale Analysis Purpose: The characterization of liver tumors is of therapeutic and prognostic relevance. Although ltrasound offers the opportunity to detect hepatic tumors, its previous techniques did not lead towards a definitve differentiation. The purpouse of this study was the evaluation of contrast enhanced ultrasound followed by quantitative digital analysis in patients with focal hepatic tumors. Materials and Methods: In a prospective stuy, 50 patients with liver tumors previously detected by CT or MRI were examined by ultrasound of the upper abdomen using conventional and phase inversion technique after intravenous application of an ultrasound contrast agent. Digital images were stored over 120 s and software powerd digital gray-scale curves were produced for each individual lesion. Results: While the percentage of tumors correctly characterised by CT/MRI amounted to 78%, the percentage increased from 60% using conventional ultrasound to 86% using contrast enhanced ultrasound including gray-scale analysis. Typical graphs were achieved for different tumor entities on digital gray-scale analysis. Time intervals at 20 and 100 seconds showed optimal for differantiation between particualar entities. Conclusion: Quantification of contrast enhanced ultrasound is an addition to the previous diagnostic procedure in hepatic tumors. It offers the possibility of an investigator-independent characterization of lesions and should be evaluated in further studies.
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