most citedW-Net: Dense Semantic Segmentation of Subcutaneous Tissue in Ultrasound Images by Expanding U-Net to Incorporate Ultrasound RF Waveform Data

1 citations · 1 across the 1 of their papers we have counts for

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2 papers

eess.IV2020★ 1 cited

W-Net: Dense Semantic Segmentation of Subcutaneous Tissue in Ultrasound Images by Expanding U-Net to Incorporate Ultrasound RF Waveform Data

Gautam Rajendrakumar Gare, Jiayuan Li, Rohan Joshi +5

We present W-Net, a novel Convolution Neural Network (CNN) framework that employs raw ultrasound waveforms from each A-scan, typically referred to as ultrasound Radio Frequency (RF…

cs.CV2018

RIFT: Multi-modal Image Matching Based on Radiation-invariant Feature Transform

Jiayuan Li, Qingwu Hu, Mingyao Ai

Traditional feature matching methods such as scale-invariant feature transform (SIFT) usually use image intensity or gradient information to detect and describe feature points; how…