Skin lesion classification from dermoscopic images using deep learning techniques

The recent emergence of deep learning methods for medical image analysis has enabled the development of intelligent medical imaging-based diagnosis systems that can assist the human expert in making better decisions about a patient’s health. In this paper we focus on the problem of skin lesion classification, particularly early melanoma detection, and present a deep-learning based approach to solve the problem of classifying a dermoscopic image containing a skin lesion as malignant or benign. The proposed solution is built around the VGGNet convolutional neural network architecture and uses the transfer learning paradigm. Experimental results are encouraging: on the ISIC Archive dataset, the proposed method achieves a sensitivity value of 78.66%, which is significantly higher than the current state of the art on that dataset.Postprint (author's final draft

11. Looking Back

From Alumni Views, Robert H. Bluestein (’67), “ILR addressed the social and economic issues of the times and sought to provide students with the tools to find solutions to many of the problems confronting society in the mid-to late-sixties. This was a period easily described as volatile, evolutionary, and sometimes revolutionary. As would have been the case at any vibrant institution, the curriculum and the students at ILR reflected those times.” Includes: Alumni Views of ILR; The Creation of the Alpern Scholarship and Prize; and A Professor’s Perspective

Anisotropic expansion of a thermal dipolar Bose gas

We report on the anisotropic expansion of ultracold bosonic dysprosium gases at temperatures above quantum degeneracy and develop a quantitative theory to describe this behavior. The theory expresses the post-expansion aspect ratio in terms of temperature and microscopic collisional properties by incorporating Hartree-Fock mean-field interactions, hydrodynamic effects, and Bose-enhancement factors. Our results extend the utility of expansion imaging by providing accurate thermometry for dipolar thermal Bose gases, reducing error in expansion thermometry from tens of percent to only a few percent. Furthermore, we present a simple method to determine scattering lengths in dipolar gases, including near a Feshbach resonance, through observation of thermal gas expansion.Comment: main text and supplement, 11 pages total, 4 figure

The impact of segmentation on the accuracy and sensitivity of a melanoma classifier based on skin lesion images

Postprint (published version

RNA-binding proteins to assess gene expression states of co-cultivated cells in response to tumor cells

BACKGROUND: Tumors and complex tissues consist of mixtures of communicating cells that differ significantly in their gene expression status. In order to understand how different cell types influence one another's gene expression, it will be necessary to monitor the mRNA profiles of each cell type independently and to dissect the mechanisms that regulate their gene expression outcomes. RESULTS: In order to approach these questions, we have used RNA-binding proteins such as ELAV/Hu, poly (A) binding protein (PABP) and cap-binding protein (eIF-4E) as reporters of gene expression. Here we demonstrate that the epitope-tagged RNA binding protein, PABP, expressed separately in tumor cells and endothelial cells can be used to discriminate their respective mRNA targets from mixtures of these cells without significant mRNA reassortment or exchange. Moreover, using this approach we identify a set of endothelial genes that respond to the presence of co-cultured breast tumor cells. CONCLUSION: RNA-binding proteins can be used as reporters to elucidate components of operational mRNA networks and operons involved in regulating cell-type specific gene expression in tissues and tumors

NeBula: TEAM CoSTAR’s robotic autonomy solution that won phase II of DARPA subterranean challenge

This paper presents and discusses algorithms, hardware, and software architecture developed by the TEAM CoSTAR (Collaborative SubTerranean Autonomous Robots), competing in the DARPA Subterranean Challenge. Specifically, it presents the techniques utilized within the Tunnel (2019) and Urban (2020) competitions, where CoSTAR achieved second and first place, respectively. We also discuss CoSTAR’s demonstrations in Martian-analog surface and subsurface (lava tubes) exploration. The paper introduces our autonomy solution, referred to as NeBula (Networked Belief-aware Perceptual Autonomy). NeBula is an uncertainty-aware framework that aims at enabling resilient and modular autonomy solutions by performing reasoning and decision making in the belief space (space of probability distributions over the robot and world states). We discuss various components of the NeBula framework, including (i) geometric and semantic environment mapping, (ii) a multi-modal positioning system, (iii) traversability analysis and local planning, (iv) global motion planning and exploration behavior, (v) risk-aware mission planning, (vi) networking and decentralized reasoning, and (vii) learning-enabled adaptation. We discuss the performance of NeBula on several robot types (e.g., wheeled, legged, flying), in various environments. We discuss the specific results and lessons learned from fielding this solution in the challenging courses of the DARPA Subterranean Challenge competition.Peer ReviewedAgha, A., Otsu, K., Morrell, B., Fan, D. D., Thakker, R., Santamaria-Navarro, A., Kim, S.-K., Bouman, A., Lei, X., Edlund, J., Ginting, M. F., Ebadi, K., Anderson, M., Pailevanian, T., Terry, E., Wolf, M., Tagliabue, A., Vaquero, T. S., Palieri, M., Tepsuporn, S., Chang, Y., Kalantari, A., Chavez, F., Lopez, B., Funabiki, N., Miles, G., Touma, T., Buscicchio, A., Tordesillas, J., Alatur, N., Nash, J., Walsh, W., Jung, S., Lee, H., Kanellakis, C., Mayo, J., Harper, S., Kaufmann, M., Dixit, A., Correa, G. J., Lee, C., Gao, J., Merewether, G., Maldonado-Contreras, J., Salhotra, G., Da Silva, M. S., Ramtoula, B., Fakoorian, S., Hatteland, A., Kim, T., Bartlett, T., Stephens, A., Kim, L., Bergh, C., Heiden, E., Lew, T., Cauligi, A., Heywood, T., Kramer, A., Leopold, H. A., Melikyan, H., Choi, H. C., Daftry, S., Toupet, O., Wee, I., Thakur, A., Feras, M., Beltrame, G., Nikolakopoulos, G., Shim, D., Carlone, L., & Burdick, JPostprint (published version

1974

History of Golf (1) The Nine Toughest Holes in the World (2) Stockie Madness (3) Bartender, One More Round for Pythium (3) Panel: 1973 Turf Problems in Review - 1974 Possible Remedies (A1-A12) Movement of Water to a Holding Pond (A13) Maintenance of Low Budget, Short Season Golf Courses (A16) Turfgrass Fertilization (A18) Determining Turfgrass Fertilizer Needs (A25) Shortage of Plant Food and How to Adjust to Supply and Cost (A29) Panel: Tricalcium Arsenate - Use and Abuse (A33-A46) Operating and Maintaining Municipal Golf Courses (A48) Maintenance of a High Budget Golf Course (A51) Trends in Agricultural Education and Where Are the Emphases (A58) Maintenance of Municipal Parks and Recreation Areas (A60) Maintenance of Grass Tennis Courts (A63) Transition from Natural to Artificial Turf (A67) Plant materials for Outlying Areas (A71) Care of University Grounds (A76) Maintenance of Industrial Sites (A79) Turfgrass Diseases and Systemic Fungicides (A81) A Look at the Future (A 84) Watering of Golf Course Turf (A92

Novel therapeutic approaches for pulmonary fibrosis

Pulmonary fibrosis represents the end stage of a number of heterogeneous conditions and is, to a greater or lesser degree, the hallmark of the interstitial lung diseases. It is characterized by the excessive deposition of extracellular matrix proteins within the pulmonary interstitium leading to the obliteration of functional alveolar units and in many cases, respiratory failure. While a small number of interstitial lung diseases have known aetiologies, most are idiopathic in nature, and of these, idiopathic pulmonary fibrosis is the most common and carries with it an appalling prognosis – median survival from the time of diagnosis is less than 3 years. This reflects the lack of any effective therapy to modify the course of the disease, which in turn is indicative of our incomplete understanding of the pathogenesis of this condition. Current prevailing hypotheses focus on dysregulated epithelial–mesenchymal interactions promoting a cycle of continued epithelial cell injury and fibroblast activation leading to progressive fibrosis. However, it is likely that multiple abnormalities in a myriad of biological pathways affecting inflammation and wound repair – including matrix regulation, epithelial reconstitution, the coagulation cascade, neovascularization and antioxidant pathways – modulate this defective crosstalk and promote fibrogenesis. This review aims to offer a pathogenetic rationale behind current therapies, briefly outlining previous and ongoing clinical trials, but will focus on recent and exciting advancements in our understanding of the pathogenesis of idiopathic pulmonary fibrosis, which may ultimately lead to the development of novel and effective therapeutic interventions for this devastating condition