Medical Image Segmentation Based on Multi-Modal Convolutional Neural Network: Study on Image Fusion Schemes

Image analysis using more than one modality (i.e. multi-modal) has been increasingly applied in the field of biomedical imaging. One of the challenges in performing the multimodal analysis is that there exist multiple schemes for fusing the information from different modalities, where such schemes are application-dependent and lack a unified framework to guide their designs. In this work we firstly propose a conceptual architecture for the image fusion schemes in supervised biomedical image analysis: fusing at the feature level, fusing at the classifier level, and fusing at the decision-making level. Further, motivated by the recent success in applying deep learning for natural image analysis, we implement the three image fusion schemes above based on the Convolutional Neural Network (CNN) with varied structures, and combined into a single framework. The proposed image segmentation framework is capable of analyzing the multi-modality images using different fusing schemes simultaneously. The framework is applied to detect the presence of soft tissue sarcoma from the combination of Magnetic Resonance Imaging (MRI), Computed Tomography (CT) and Positron Emission Tomography (PET) images. It is found from the results that while all the fusion schemes outperform the single-modality schemes, fusing at the feature level can generally achieve the best performance in terms of both accuracy and computational cost, but also suffers from the decreased robustness in the presence of large errors in any image modalities.Comment: Zhe Guo and Xiang Li contribute equally to this wor

Glucocorticoid induced leucine zipper is required for adipogenesis and is a target for the anti-adipogenic activities of oncostatin m

Thesis (Ph.D.)--Boston UniversityFat cell development is a dynamic cellular transition process in which committed preadipocytes convert to adipocytes. The initial goal of my research was to identify repressed gene programs in adipogenesis, and to test the hypothesis that these repressed gene programs suppress adipogenesis. Using microarray analyses of 3T3-L1 cells, we found that the expression of gene programs, most notably cytokines/chemokines, correlated inversely with the differentiation state. We analyzed the effect of different components of the adipogenic hormonal cocktail in 3T3-L1 preadipocytes. It was found that dexamethasone (Dex) acting through the glucocorticoid receptor (GR) was a major suppressor of the cytokine expression. In our efforts to characterize roles for glucocorticoid signaling in adipogenesis, we found that glucocorticoid-induced leucine zipper (GILZ), a target of GR, was required for adipogenesis in both 3T3-L1 preadipocytes and C3H10T1/2 mesenchymal stem cells (MSCs). We also showed that GILZ was required for bone morphogenic protein 4 (BMP4)-induced white adipocyte differentiation and BMP7-induced brown differentiation in C3H10T1/2 MSCs. In a gain-of-function study, GILZ overexpression (OE) had minimal effects on normal adipogenesis in 3T3-L1 preadipocytes, but increased adipogenic gene expression in C3H10T1/2 MSCs. Oncostatin M (OSM) is an anti-adipogenic cytokine. When exploring mechanisms governing the anti-adipogenic activity of OSM and testing the hypothesis that GILZ is a target for OSM, we found that while OSM inhibited the expression of endogenous GILZ, ectopically expressed GILZ overrode OSM's effect in suppressing adipocyte development, suggesting GILZ is a target of the anti-adipogenic activity of OSM. During our studies to find signaling pathways regulating the interplay between GILZ and OSM, we found that OSM induced both ERK and STAT5 phosphorylation, but only inhibition of ERK activity by U0126 partially abolished OSM's inhibition on GILZ expression. Taken together, we identified a cytokine/chemokine program that is downregulated in adipogenesis. Dex-GR-GILZ signaling pathway played an essential role in suppressing the cytokine program and is required for adipogenesis. OSM inhibited adipogenesis by suppressing expression of GILZ, which is mediated by the activation of ERK phosphorylation. These findings highlighted the critical role of GILZ m adipogenesis and can contribute to combating metabolic disorders such as obesity