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Motorola Solutions Foundation Scholars Program

Accepted Students – 2021




Ashley Calles

Hello! My name’s Ashley Calles. I’m currently a Junior at DePaul University, majoring in Computer Science and minoring in Math and Data Science. My current research project is on a computer-aided diagnosis of lung nodules.  When not working on research or classwork, I enjoy hiking, snowboarding, and reading.

BS in Computer Science

Stan Raicu, Daniela

acalles1@depaul.edu



Project: Computer-aided Diagnosis Systems for Lung Nodule Classification: Taking Into Consideration Semantic Features


Lung cancer is a leading cause of cancer death in both men and women, making up almost 25% of all cancer deaths. While significant progress has been made to advance binary computer-aided diagnosis (CAD) systems (highly malignant versus highly benign), there is still a need to predict the degree of malignancy as the hard to classify cases are the ones that are typically uncertain (somehow benign, indeterminant, somehow malignant).  We hypothesize that by integrating domain knowledge, such as semantic characteristics used by medical experts to describe the visual appearance of lung nodules, the performance of the CAD systems can be further improved. Using the NIH/NCI Lung Image Database Consortium (LIDC) image collection, we show that there is a strong correlation between semantic characteristics and malignancy. In our preliminary results, we found that there is a high correlation between speculation and malignancy. Using Yule’s Q, Goodman & Kruskal’s Gamma, and Spearman’s Rho correlation methods, we found the correlation between speculation and malignancy to be 0.87, 0.75, and 0.65 respectively. Establishing the relationship between the semantic characteristics is critical since this additional information about the characteristics can be used to further improve CAD performance.

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