Computer aid diagnosis for brain MRI image is widely used in hospitals. An important step in it is to recognize different regions within an MRI image according to medical experience. In this paper, we propose an unsupervised learning algorithm for automatic segmentation of MRI images. Different from previous methods, our method achieves the idea of visual segmentation, which simulates the think...

Region-based image segmentation techniques make use of similarity in intensity, color and texture to determine the partitioning of an image. The powerful cue of contour continuity is not exploited at all. In this paper, we provide a way of incorporating curvilinear grouping into region-based image segmentation. Soft contour information is obtained through orientation energy. Weak contrast gaps ...

The aim of this paper is to present an improvement of a previously published algorithm. The proposed approach is performed in two steps. In the first step, we generate the Weighted Adaptive Neighborhood Hypergraph (WAINH) of the given gray-scale image. In the second step, we partition the WAINH using a multilevel hypergraph partitioning technique. To evaluate the algorithm performances, experim...

Compact and wide stopband lowpass filter with high suppression level using corrugated high impedance transmission line with symmetrically loaded multiple patch resonators is designed and demonstrated. The measured results validate the simulated characteristics and exhibit a roll-off of 60 dB/GHz and a wide stopband with suppression level better than 31 dB from 2.65 GHz to 13.4 GHz. The 3 dB cut...

A 27-year-old female was referred with an abdominal mass. Examination revealed a non tender firm mass in the right flank and hypertension (200/100 mmHg). An angiomyolipoma was suspected on computed tomography and arteriography and a radical nephrectomy was performed. On cut section, the kidney was occupied by a well-capsulated, grayish tumor measuring 10 x 9 cm. Pathological diagnosis was a ren...

This paper proposes an unsupervised method for material classification of raw printed circuit boards (PCBs) based on the dimension-reduced spectral information. First, a spectral imaging system is constructed for acquiring precise spectral reflectance images. Only 3-dimensional spectral features are then extracted from the original 31-dimensional spectral image data by PCA for segmentation prop...

Spectral clustering has been widely used due to its simplicity for solving graph clustering problem in recent years. However, it suffers from the high computational cost as data grow in scale, and is limited by the performance of post-processing. To address these two problems simultaneously, in this paper, we propose a novel approach denoted by orthogonal and nonnegative graph reconstruction (O...

If we have found a ”good” clustering C of a data set, can we prove that C is not far from the (unknown) best clustering C of these data? Perhaps surprisingly, the answer to this question is sometimes yes. This paper proves spectral bounds on the distance d(C, C) for the case when “goodness” is measured by a quadratic cost, such as the squared distortion of K-means clustering, or the Normalized ...