Search Results
Semantic segmentation of non-linear multimodal images for disease grading of inflammatory bowel disease: A segnet-based application
2019, Pradhan, Pranita, Meyer, Tobias, Vieth, Michael, Stallmach, Andreas, Waldner, Maximilian, Schmitt, Michael, Popp, Juergen, Bocklitz, Thomas, De Marsico, Maria, Sanniti di Baja, Gabriella, Fred, Ana
Non-linear multimodal imaging, the combination of coherent anti-stokes Raman scattering (CARS), two-photon excited fluorescence (TPEF) and second harmonic generation (SHG), has shown its potential to assist the diagnosis of different inflammatory bowel diseases (IBDs). This label-free imaging technique can support the ‘gold-standard’ techniques such as colonoscopy and histopathology to ensure an IBD diagnosis in clinical environment. Moreover, non-linear multimodal imaging can measure biomolecular changes in different tissue regions such as crypt and mucosa region, which serve as a predictive marker for IBD severity. To achieve a real-time assessment of IBD severity, an automatic segmentation of the crypt and mucosa regions is needed. In this paper, we semantically segment the crypt and mucosa region using a deep neural network. We utilized the SegNet architecture (Badrinarayanan et al., 2015) and compared its results with a classical machine learning approach. Our trained SegNet mod el achieved an overall F1 score of 0.75. This model outperformed the classical machine learning approach for the segmentation of the crypt and mucosa region in our study.
A Computational Pipeline for Sepsis Patients’ Stratification and Diagnosis
2018, Campos, David, Pinho, Renato, Neugebauer, Ute, Popp, Juergen, Oliveira, José Luis, Zwiggelaar, Reyer, Gamboa, Hugo, Fred, Ana, Bermúdez i Badia, Sergi
Sepsis is still a little acknowledged public health issue, despite its increasing incidence and the growing mortality rate. In addition, a clear diagnosis can be lengthy and complicated, due to highly variable symptoms and non-specific criteria, causing the disease to be diagnosed and treated too late. This paper presents the HemoSpec platform, a decision support system which, by collecting and automatically processing data from several acquisition devices, can help in the early diagnosis of sepsis.
Frequency dependence of magnetothermal properties for magnetic fluid and magnetically functionalized implants
2018, Salakhova, R.T., Vylegzhanin, A. G., Kashtanov, E.A., Zverev, V.I., Müller, R., de Sena Pereira, F.D., Parfenov, V.A., Mironov, V.A., Kritskaya, E.A., Pyatakov, A.P., Markov, V.K., Malyshev, A.Yu, Kamilov, K.I, Tishin, A.M, Perov, N., Semisalova, A.
Heating of the magnetic nanoparticles in AC magnetic field is the effect promising for application in medicine. The mechanisms of heating in AC-magnetic field implies nontrivial dependence of the power dissipated by magnetic nanoparticles on frequency. With the use of a reconfigurable experimental setup, this frequency-dependent magnetic heating was measured on two characteristic examples: the magnetite nanoparticles conventionally used in medicine and polymer coating with micrometer sized magnetite particles. The saturation of the heating power with frequency is shown that is more pronounced for the second case of microparticles.