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Previous studies by our group have shown that 3-D high-frequency quantitative ultrasound (QUS) methods have the potential to differentiate metastatic lymph nodes (LNs) from cancer-free LNs dissected from human cancer patients. To successfully perform these methods inside the LN parenchyma (LNP), an automatic segmentation method is highly desired to exclude the surrounding thin layer of fat from QUS...
Clinical Decision Support (CDS) aids in early diagnosis of liver cancer, a potentially fatal disease prevalent in both developed and developing countries. Our research aims to develop a robust and intelligent clinical decision support framework for disease management of cancer based on legacy Ultrasound (US) image data collected during various stages of liver cancer. The proposed intelligent CDS framework...
The risk of breast cancer in women increases notably with age; one of every eight women is prone to get breast cancer in her lifetime. Ultrasonography is a noninvasive and painless medical imaging technique which achieves high lesion detection accuracy. However, ultrasound images are characterized by their specular nature, attenuation, speckle, shadows, and low contrast. This work proposes a six step...
Image segmentation is an important task in medical image analysis. Automatic segmentation of ultrasound image is a difficult task as it suffers from speckle noise. This paper presents a fully automatic approach in which there is no need for the user to provide a seed point to segment the image. It proposes a new method for segmenting the fibroid in uterus. The method used in this paper uses concepts...
In order to address the tendency of ultrasound B-Mode images to show a too small sizing of tumour masses in breast cancer diagnosis, a novel segmentation method has been introduced. In this paper it has been explored if this problem can be solved by incorporating strain parameters from ultrasound elastography into a segmentation framework. By incorporating a local power estimate from an autoregressive...
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