Model-Based Deep Learning

Signal processing, communications, and control have traditionally relied on classical statistical modeling techniques. Such model-based methods utilize mathematical formulations that represent the underlying physics, prior information and additional domain knowledge. Simple classical models are useful but sensitive to inaccuracies and may lead to poor performance when real systems display complex or dynamic behavior. On the other hand, purely data-driven approaches that are model-agnostic are becoming increasingly popular as datasets become abundant and the power of modern deep learning pipelines increases. Deep neural networks (DNNs) use generic architectures which learn to operate from data, and demonstrate excellent performance, especially for supervised problems. However, DNNs typically require massive amounts of data and immense computational resources, limiting their applicability for some signal processing scenarios. We are interested in hybrid techniques that combine principled mathematical models with data-driven systems to benefit from the advantages of both approaches. Such model-based deep learning methods exploit both partial domain knowledge, via mathematical structures designed for specific problems, as well as learning from limited data. In this article we survey the leading approaches for studying and designing model-based deep learning systems. We divide hybrid model-based/data-driven systems into categories based on their inference mechanism. We provide a comprehensive review of the leading approaches for combining model-based algorithms with deep learning in a systematic manner, along with concrete guidelines and detailed signal processing oriented examples from recent literature. Our aim is to facilitate the design and study of future systems on the intersection of signal processing and machine learning that incorporate the advantages of both domains

Reverse and pseudoreverse cortical sign in thoracolumbar burst fracture: radiologic description and distinction—a propos of three cases

In thoracolumbar burst fracture the “reverse cortical sign” is a known entity that corresponds to a fragment of the posterior wall that has been flipped 180° with the cancellous surface of the fragment facing posteriorly in the canal and the cortical surface (posterior wall) facing anteriorly. The identification of such reverse cortical fragment is crucial as ligamentotaxis is classically contraindicated as the posterior longitudinal ligament is ruptured. Recognition of such a flipped cortical fragment has relied so far on the axial CT. The advent of CT scans with sagittal reconstruction has allowed us to better describe such entities that have received little attention in the literature. The goal of this report was therefore to describe the appearance of the reverse cortical sign and its likes as they can appear on axial CT scans, sagittal reconstructions and MRI. During 1-year practice at our institution we had to treat three patients with thoracolumbar burst fracture associated with what looked like a reverse cortical sign on the axial CT scans. Further analysis of the sagittal reconstruction CT could differentiate the true reverse cortical sign from a new entity that we coined “the pseudoreverse cortical sign” as observed in two out of the three cases. In the pseudo reverse cortical sign what appears to be a flipped piece of posterior vertebral body is actually part of the superior or inferior endplate that is depressed into the comminuted vertebral body. In such cases the posterior longitudinal ligament appears to be in continuity and therefore such fracture can theoretically be treated with posterior ligamentotaxis as evidenced in one of our case. Careful analysis of the CT scan and specifically the sagittal reconstruction and MRI can differentiate two separate entities that may correspond to a different severity injury

Mixed Metastatic Lung Cancer Lesions in Bone Are Inhibited by Noggin Overexpression and Rank:Fc Administration

UNLABELLED: Lung cancer metastases to bone produce a primarily mixed osteolytic/osteoblastic lesion. The purpose of this study was to determine if blockade of both pathways would inhibit the formation these lesions in bone. Inhibition of the osteoblastic lesion with noggin and the osteolytic lesion with RANK:Fc was a successful treatment strategy to inhibit progression of mixed lung cancer lesions in bone.\ud \ud INTRODUCTION: Approximately 9-30% of patients with lung cancer develop bone metastases, leading to significant morbidity and mortality. A549 is a non-small-cell lung cancer (NSCLC) line that produces a mixed metastatic lesion in bone. We sought to determine if blockade of key components in both osteolytic and osteoblastic pathways would result in a reduction of a NSCLC tumor progression in a murine model of bony metastasis.\ud \ud MATERIALS AND METHODS: The study used a retroviral vector overexpressing noggin (RN), a specific inhibitor of BMP, and RANK:Fc, a chimeric protein that inhibits the RANK-RANKL interaction. A549 cells were transduced with RN before implantation in SCID mice. Cells were implanted in a subcutaneous model and tibial injection model. RANK:Fc was administered twice weekly at 15 mg/kg. There were five treatment groups: A549; A549 + RN; A549 + RANK:Fc; A549 + empty vector; and A549 + RN + RANK:Fc (n = 10/group).\ud \ud RESULTS: In SCID mice who underwent subcutaneous A549 tumor cell injection, animals treated with A549 + RN had significantly smaller subcutaneous tumor size at 8 weeks. In an intratibial model of bony metastasis, animals injected with A549 cells developed a mixed lytic/blastic lesion with cortical destruction at 8 weeks. Treatment with RANK:Fc inhibited the formation of osteoclasts, led to a smaller tumor volume in bone, and inhibited the lytic component of the mixed lesion. Animals treated with A549 + RN had a decreased number of osteoblasts in bone lesions, smaller tumor volume, and inhibition of the blastic component of the mixed lesions. Combination treatment inhibited both the lytic and blastic components of the lesion.\ud \ud CONCLUSIONS: The NSCLC cell line A549 forms a mixed osteolytic/osteoblastic lesion in vivo. Noggin overexpression inhibited the formation of the osteoblastic aspect of the lesion in bone and the tumor growth in vivo. Treatment with RANK:Fc limited the formation of the lytic aspect of the mixed lesion and also inhibited the rate of in vivo tumor growth. Inhibition of both pathways is necessary to effectively inhibit the progression of mixed metastatic lesions in bone.\ud \u