Xu Li

Biomedical Engineering · IEEE Transactions on Biomedical Engineering · 2001–2005

A researcher in the Science corpus: 4 papers; trusts 3 researchers and is trusted by 17 researchers here, as inferred from the citation graph.

Subfields

Whom Xu Li trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Elise C. Fear
  2. Susan C. Hagness
  3. Maria A. Stuchly
  4. Essex J. Bond

Who trusts Xu Li overall

  1. Elise C. Fear
  2. Rohit Chandra
  3. Hooi Been Lim
  4. Amin Abbosh
  5. Susan C. Hagness
  6. Jeff M. Sill
  7. M. Klemm
  8. Essex J. Bond
  9. Huiyuan Zhou
  10. Nguyen Thi Tuyet Nhung

Papers from Xu Li's perspective

Ordered by how strongly the researchers Xu Li trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Microwave imaging via space-time beamforming for early detection of breast cancer (IEEE International Conference on Acoustics, Speech, and Signal Processing)
  2. Adaptive Filter Theory
  3. Confocal microwave imaging for breast cancer detection: localization of tumors in three dimensions (IEEE Transactions on Biomedical Engineering)
  4. [신간안내] Computational Electrodynamics (the finite difference time - domain method)
  5. A confocal microwave imaging algorithm for breast cancer detection (IEEE Microwave and Wireless Components Letters)
  6. A large-scale study of the ultrawideband microwave dielectric properties of normal, benign and malignant breast tissues obtained from cancer surgeries (Physics in Medicine and Biology)
  7. A large-scale study of the ultrawideband microwave dielectric properties of normal breast tissue obtained from reduction surgeries (Physics in Medicine and Biology)
  8. An overview of ultra-wideband microwave imaging via space-time beamforming for early-stage breast-cancer detection (IEEE Antennas & Propagation Magazine)
  9. Tissue Sensing Adaptive Radar for Breast Cancer Detection—Experimental Investigation of Simple Tumor Models (IEEE transactions on microwave theory and techniques)
  10. Enhancing breast tumor detection with near-field imaging

Their papers