25 citations · 54 across the 4 of their papers we have counts for
5 papers
Convolutional Neural Networks for Histopathology Image Classification: Training vs. Using Pre-Trained Networks
Brady Kieffer, Morteza Babaie, Shivam Kalra +1
We explore the problem of classification within a medical image data-set based on a feature vector extracted from the deepest layer of pre-trained Convolution Neural Networks. We h…
A Comparative Study of CNN, BoVW and LBP for Classification of Histopathological Images
Meghana Dinesh Kumar, Morteza Babaie, Shujin Zhu +2
Despite the progress made in the field of medical imaging, it remains a large area of open research, especially due to the variety of imaging modalities and disease-specific charac…
Skin Lesion Segmentation: U-Nets versus Clustering
Bill S. Lin, Kevin Michael, Shivam Kalra +1
Many automatic skin lesion diagnosis systems use segmentation as a preprocessing step to diagnose skin conditions because skin lesion shape, border irregularity, and size can influ…
Learning Autoencoded Radon Projections
Aditya Sriram, Shivam Kalra, H. R. Tizhoosh +1
Autoencoders have been recently used for encoding medical images. In this study, we design and validate a new framework for retrieving medical images by classifying Radon projectio…
Classification and Retrieval of Digital Pathology Scans: A New Dataset
Morteza Babaie, Shivam Kalra, Aditya Sriram +5
In this paper, we introduce a new dataset, \textbf{Kimia Path24}, for image classification and retrieval in digital pathology. We use the whole scan images of 24 different tissue t…