Professorial Advancement Initiative: A Cross-Institutional Collaboration to Increase Faculty Diversity in STEM.

In this paper, we describe the model for faculty diversity developed as part of the Professorial Advancement Initiative (PAI) funded under the NSF AGEP program. The PAI, consisting of 12 of the 14 Big Ten Academic Alliance universities, had the goal of doubling the rate at which the universities hired tenure-track minoritized faculty, defined by National Science Foundation as African Americans, Hispanic/Latinx, Native Americans, and Pacific Islanders. This paper reviews the key programmatic elements of the PAI and discusses lessons learned and the practices developed that helped the Alliance achieve its faculty diversity goal.

Efficient block-based frequency domain wavelet transform implementations.

Subband decompositions for image coding have been explored extensively over the last few decades. The condensed wavelet packet (CWP) transform is one such decomposition that was recently shown to have coding performance advantages over conventional decompositions. A special feature of the CWP is that its design and implementation are performed in the cyclic frequency domain. While performance gains have been reported, efficient implementations of the CWP (or more generally, efficient implementations of cyclic filter banks) have not yet been fully explored. In this paper, we present efficient block-based implementations of cyclic filter banks along with an analysis of the arithmetic complexity. Block-based cyclic filter bank implementations of the CWP coder are compared with conventional subband/wavelet image coders whose filter banks are implemented in the time domain. It is shown that block-based cyclic filter bank implementations can result in CWP coding systems that outperform the popular image coding systems both in terms of arithmetic complexity and coding performance.

A new method for registration-based medical image interpolation.

A new technique is presented for interpolating between grey-scale images in a medical data set. Registration between neighboring slices is achieved with a modified control grid interpolation algorithm that selectively accepts displacement field updates in a manner optimized for performance. A cubic interpolator is then applied to pixel intensities correlated by the displacement fields. Special considerations are made for efficiency, interpolation quality, and compression in the implementation of the algorithm. Experimental results show that the new method achieves good quality, while offering dramatic improvement in efficiency relative to the best competing method.

New perspectives and improvements on the symmetric extension filter bank for subband/wavelet image compression.

In subband/wavelet image coding, size-limited subband decompositions are ordinarily used to avoid increasing the number of samples that need to be coded. To reduce coding distortions that can occur at the borders, the symmetric extension filter bank is typically employed. This paper introduces some new perspectives and improvements to that decomposition. The symmetric extension filter bank is couched in the cyclic frequency domain, providing a framework that accommodates FIR and IIR filters in a natural way, all with perfect reconstruction. IIR filters with both rational and irrational transfer functions can be implemented and, in the context of symmetric extension, can accommodate IIRs that effectively have perfect stopband suppression. Enhancements to the filter bank at a tree-structured system level are also presented and include the application of spectral reversal correction and a transition band normalization approach to designing the constituent filters of the symmetric extension wavelet packet transform.

Application of an adaptive control grid interpolation technique to morphological vascular reconstruction.

The problem of interslice magnetic resonance (MR) image reconstruction arises in a broad range of medical applications. In such cases, there is a need to approximate information present in the original subject that is not reflected in contiguously acquired MR images because of hardware sampling limitations. In the context of vascular morphology reconstruction, this information is required in order for subsequent visualization and computational analysis of blood vessels to be most effective. Toward that end we have developed a method of vascular morphology reconstruction based on adaptive control grid interpolation (ACGI) to function as a precursor to visualization and computational analysis. ACGI has previously been implemented in addressing various problems including video coding and tracking. This paper focuses on the novel application of the technique to medical image processing. ACGI combines features of optical flow-based and block-based motion estimation algorithms to enhance insufficiently dense MR data sets accurately with a minimal degree of computational complexity. The resulting enhanced data sets describe vascular geometries. These reconstructions can then be used as visualization tools and in conjunction with computational fluid dynamics (CFD) simulations to offer the pressure and velocity information necessary to quantify power loss. The proposed ACGI methodology is envisioned ultimately to play a role in surgical planning aimed at producing optimal vascular configurations for successful surgical outcomes.

Improved structures of maximally decimated directional filter banks for spatial image analysis.

This paper introduces an improved structure for directional filter banks (DFBs) that preserves the visual information in the subband domain. The new structure achieves this outcome while preserving both the efficient polyphase implementation and the exact reconstruction property. The paper outlines a step-by-step framework in which to examine the DFB, and within this framework discusses how, through the insertion of post-sampling matrices, visual distortions can be removed. In addition to the efficient tree structure, attention is given to the form and design of efficient linear phase filters. Most notably, linear phase IIR prototype filters are presented, together with the design details. These filters can enable the DFB to have more than a three-fold improvement in complexity reduction over quadrature mirror filters (QMFs).

Two-band hybrid FIR-IIR filters for image compression.

Two-band analysis-synthesis filters or wavelet filters are used pervasively for compressing natural images. Both FIR and IIR filters have been studied in this context, the former being the most popular. In this paper, we examine the compression performance of these two-band filters in a dyadic wavelet decomposition and attempt to isolate features that contribute most directly to the performance gain. Then, employing the general exact reconstruction condition, hybrid FIR-IIR analysis-synthesis filters are designed to maximize compression performance for natural images. Experimental results are presented that compare performance with the popular biorthogonal filters in terms of peak SNR, subjective quality, and computational complexity.

A two-channel overlapped block transform for image compression.

In this correspondence, a new two-channel overlapped block transform is introduced by prefiltering the Haar transform. The prefiltering employs plane rotations with one single rotation angle to achieve high computational efficiency. The resulting transform is equivalent to a periodically time-varying (PTV) filter bank. The proposed transform or PTV filter bank has several advantages for image coding. First, symmetric extension is very easily performed at the boundaries in spite of the fact that the filters are asymmetric. Second, arithmetic complexity can be reduced to simple shifts and adds. Finally, the performance for image compression is shown to be high, both in terms of visual quality and PSNR. As a result, the proposed transform is a competitive alternative to the 5/3 and the 9/7 filters, which are currently popular for subband/wavelet image coders.

New techniques for the reconstruction of complex vascular anatomies from MRI images.

The accurate representation of two-dimensional images in three dimensions has become important for many medical imaging applications and for cardiac magnetic resonance imaging (MRI) in particular. Reconstruction methods applied after data acquisition can produce three-dimensional information from two-dimensional data and make applications such as surgical planning more effective. Current reconstruction techniques usually demand contrast agents, and can suffer due to poor segmentation and sampling constraints that cause surface irregularities and distort dimensions. The novel technique presented here for anatomical modeling uses adaptive control grid interpolation (ACGI) to approximate data not captured by scanning, and a progressive shape-element segmentation technique to complete reconstruction. Quantitative validations conducted on models of pediatric cardiac malformations have confirmed the theoretical advantages of this technique, and that higher quality is achieved than with competing methods based on geometric parameters. Vascular diameters from reconstructions showed errors of less than 1% for a known geometry as compared to over 9% for competing methods. Qualitatively, models produced with the new methodology displayed substantial improvement over alternatives. Approximately 50 rare cardiac structures, including surgically altered Fontan and atypical aortic anatomies, have been reconstructed. All data used to create these reconstructions were acquired using standard pulse sequences and without contrast agents. Benefits of the new technique are particularly evident when complex vascular configurations complicate reconstruction. The proposed methodology enables a powerful tool allowing physicians to analyze and manipulate highly accurate and clearly presented vascular structures in an interactive medium.