H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 32 Citations 4,546 100 World Ranking 6990 National Ranking 59

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Cancer
  • Radiology

His primary scientific interests are in Artificial intelligence, Breast ultrasound, Pattern recognition, Computer-aided diagnosis and Pathology. His studies in Artificial intelligence integrate themes in fields like Automated whole-breast ultrasound and Computer vision. The Breast ultrasound study combines topics in areas such as BI-RADS, Breast imaging and Speckle pattern.

Ruey-Feng Chang combines subjects such as Breast cancer and Predictive value with his study of Computer-aided diagnosis. Ruey-Feng Chang has included themes like Image quality, Radiology, Ultrasound and Receiver operating characteristic in his Pathology study. His Radiology study incorporates themes from Cancer and Surgery.

His most cited work include:

  • Computer-aided diagnosis applied to US of solid breast nodules by using neural networks. (178 citations)
  • Diagnosis of breast tumors with sonographic texture analysis using wavelet transform and neural networks (173 citations)
  • Automatic ultrasound segmentation and morphology based diagnosis of solid breast tumors. (167 citations)

What are the main themes of his work throughout his whole career to date?

His main research concerns Artificial intelligence, Radiology, Pattern recognition, Breast cancer and Computer-aided diagnosis. His research on Artificial intelligence often connects related topics like Computer vision. His Radiology research includes themes of Cancer, Mammography, Breast ultrasound and Receiver operating characteristic.

He has researched Receiver operating characteristic in several fields, including BI-RADS, Breast imaging, Region growing and Pathology. The various areas that he examines in his Breast cancer study include Segmentation, Metastasis and Cluster analysis. His Computer-aided diagnosis study which covers Second opinion that intersects with Predictive value of tests.

He most often published in these fields:

  • Artificial intelligence (47.56%)
  • Radiology (44.51%)
  • Pattern recognition (33.54%)

What were the highlights of his more recent work (between 2014-2021)?

  • Breast cancer (28.66%)
  • Radiology (44.51%)
  • Computer-aided diagnosis (29.88%)

In recent papers he was focusing on the following fields of study:

Ruey-Feng Chang mainly focuses on Breast cancer, Radiology, Computer-aided diagnosis, Artificial intelligence and Ultrasound. His Breast cancer research is multidisciplinary, relying on both Segmentation and Pathology. Ruey-Feng Chang interconnects Whole breast, Lymph node, Primary tumor, Metastasis and Electromagnetic tracking in the investigation of issues within Radiology.

His studies deal with areas such as Feature, Texture, Speckle pattern, Elastography and Receiver operating characteristic as well as Computer-aided diagnosis. His Artificial intelligence research is multidisciplinary, incorporating perspectives in Lung cancer and Pattern recognition. His research integrates issues of Rotator cuff, Breast density and Physical examination in his study of Ultrasound.

Between 2014 and 2021, his most popular works were:

  • Tumor Detection in Automated Breast Ultrasound Using 3-D CNN and Prioritized Candidate Aggregation (46 citations)
  • Computer-aided diagnosis of liver tumors on computed tomography images (44 citations)
  • Quantification of breast tumor heterogeneity for ER status, HER2 status, and TN molecular subtype evaluation on DCE-MRI. (39 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Cancer
  • Internal medicine

His primary areas of investigation include Breast cancer, Computer-aided diagnosis, Pattern recognition, Artificial intelligence and Receiver operating characteristic. The study incorporates disciplines such as Feature and Pathology in addition to Breast cancer. His Pathology research is multidisciplinary, incorporating elements of Mammography and Ultrasound.

He works mostly in the field of Pattern recognition, limiting it down to concerns involving Breast ultrasound and, occasionally, Feature extraction, Convolutional neural network and Image fusion. His study connects Computer vision and Artificial intelligence. His biological study spans a wide range of topics, including BI-RADS, Radiology, Oncology and Speckle pattern.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Top Publications

Computer-aided diagnosis applied to US of solid breast nodules by using neural networks.

Dar-Ren Chen;Ruey-Feng Chang;Yu-Len Huang.
Radiology (1999)

270 Citations

Diagnosis of breast tumors with sonographic texture analysis using wavelet transform and neural networks

Dar-Ren Chen;Ruey-Feng Chang;Wen-Jia Kuo;Ming-Chun Chen.
Ultrasound in Medicine and Biology (2002)

265 Citations

Automatic ultrasound segmentation and morphology based diagnosis of solid breast tumors.

Ruey Feng Chang;Wen Jie Wu;Wookyung Moon;Dar Ren Chen.
Breast Cancer Research and Treatment (2005)

249 Citations

Breast cancer diagnosis using self-organizing map for sonography.

Dar-Ren Chen;Ruey-Feng Chang;Yu-Len Huang.
Ultrasound in Medicine and Biology (2000)

248 Citations

Classification of breast ultrasound images using fractal feature.

Dar Ren Chen;Ruey Feng Chang;Chii Jen Chen;Ming Feng Ho.
Clinical Imaging (2005)

179 Citations

Improvement in breast tumor discrimination by support vector machines and speckle-emphasis texture analysis

Ruey Feng Chang;Wen Jie Wu;Woo Kyung Moon;Dar Ren Chen.
Ultrasound in Medicine and Biology (2003)

173 Citations

Support Vector Machines for Diagnosis of Breast Tumors on US Images

Ruey Feng Chang;Wen Jie Wu;Wookyung Moon;Yi Hong Chou.
Academic Radiology (2003)

141 Citations

3-D breast ultrasound segmentation using active contour model

Dar Ren Chen;Ruey Feng Chang;Wen Jie Wu;Wookyung Moon.
Ultrasound in Medicine and Biology (2003)

126 Citations

Data mining with decision trees for diagnosis of breast tumor in medical ultrasonic images.

Wen-Jia Kuo;Ruey-Feng Chang;Dar-Ren Chen;Cheng Chun Lee.
Breast Cancer Research and Treatment (2001)

125 Citations

Tamper detection and recovery for medical images using near-lossless information hiding technique.

Jeffery H K Wu;Ruey Feng Chang;Chii Jen Chen;Ching Lin Wang.
Journal of Digital Imaging (2008)

124 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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