Precision Learning: Towards Use of Known Operators in Neural Networks

In this paper, we consider the use of prior knowledge within neural networks. In particular, we investigate the effect of a known transform within the mapping from input data space to the output domain. We demonstrate that use of known transforms is able to change maximal error bounds. In order to explore the effect further, we consider the problem of X-ray material decomposition as an example to incorporate additional prior knowledge. We demonstrate that inclusion of a non-linear function known from the physical properties of the system is able to reduce prediction errors therewith improving prediction quality from SSIM values of 0.54 to 0.88. This approach is applicable to a wide set of applications in physics and signal processing that provide prior knowledge on such transforms. Also maximal error estimation and network understanding could be facilitated within the context of precision learning.Comment: accepted on ICPR 201

Kinect-Based Correction of Overexposure Artifacts in Knee Imaging with C-Arm CT Systems

Objective. To demonstrate a novel approach of compensating overexposure artifacts in CT scans of the knees without attaching any supporting appliances to the patient. C-Arm CT systems offer the opportunity to perform weight-bearing knee scans on standing patients to diagnose diseases like osteoarthritis. However, one serious issue is overexposure of the detector in regions close to the patella, which can not be tackled with common techniques. Methods. A Kinect camera is used to algorithmically remove overexposure artifacts close to the knee surface. Overexposed near-surface knee regions are corrected by extrapolating the absorption values from more reliable projection data. To achieve this, we develop a cross-calibration procedure to transform surface points from the Kinect to CT voxel coordinates. Results. Artifacts at both knee phantoms are reduced significantly in the reconstructed data and a major part of the truncated regions is restored. Conclusion. The results emphasize the feasibility of the proposed approach. The accuracy of the cross-calibration procedure can be increased to further improve correction results. Significance. The correction method can be extended to a multi-Kinect setup for use in real-world scenarios. Using depth cameras does not require prior scans and offers the possibility of a temporally synchronized correction of overexposure artifacts. To achieve this, we develop a cross-calibration procedure to transform surface points from the Kinect to CT voxel coordinates

A Novel Language Paradigm for Intraoperative Language Mapping: Feasibility and Evaluation

(1) Background—Mapping language using direct cortical stimulation (DCS) during an awake craniotomy is difficult without using more than one language paradigm that particularly follows the demand of DCS by not exceeding the assessment time of 4 s to prevent intraoperative complications. We designed an intraoperative language paradigm by combining classical picture naming and verb generation, which safely engaged highly relevant language functions. (2) Methods—An evaluation study investigated whether a single trial of the language task could be performed in less than 4 s in 30 healthy subjects and whether the suggested language paradigm sufficiently pictured the cortical language network using functional magnetic resonance imaging (fMRI) in 12 healthy subjects. In a feasibility study, 24 brain tumor patients conducted the language task during an awake craniotomy. The patients’ neuropsychological outcomes were monitored before and after surgery. (3) Results—The fMRI results in healthy subjects showed activations in a language-associated network around the (left) sylvian fissure. Single language trials could be performed within 4 s. Intraoperatively, all tumor patients showed DCS-induced language errors while conducting the novel language task. Postoperatively, mild neuropsychological impairments appeared compared to the presurgical assessment. (4) Conclusions—These data support the use of a novel language paradigm that safely monitors highly relevant language functions intraoperatively, which can consequently minimize negative postoperative neuropsychological outcomes

Fluorescein sodium-guided surgery of parotid gland tumors as a technical advance

Abstract Background Complete tumor removal and preservation of the facial nerve are essential in parotid gland surgery. A technical adjunct that potentially enhances the contrast between the facial nerve and the adherent tumor tissue and allows to identify residual tumor tissue could be Fluorescein Sodium. Methods Retrospective chart analysis on 7 patients with benign parotid gland lesions that were operated using Fluorescein Sodium intravenously and the application of the YELLOW 560 nm filter of the operating microscope. Safety and feasibility were evaluated. Results All tumors showed fluorescence and the rating ´contrast-enhancing´ was assigned in all cases. In 2 patients, satellite nodules were identified and resected meaning that the fluorescence staining of the tumor margins was significantly better than under white light. Conclusion The use of Fluorescein Sodium in parotidectomy is promising. In two cases residual tumor was detected that would have been left behind under white light. Further research in parotid gland surgery and other head and neck tumor procedures is warranted

Joint Superresolution and Rectification for Solar Cell Inspection

Visual inspection of solar modules is an important monitoring facility in photovoltaic power plants. Since a single measurement of fast CMOS sensors is limited in spatial resolution and often not sufficient to reliably detect small defects, we apply multiframe superresolution (MFSR) to a sequence of low-resolution measurements. In addition, the rectification and removal of lens distortion simplifies subsequent analysis. Therefore, we propose to fuse this preprocessing with standard MFSR algorithms. This is advantageous, because we omit a separate processing step, the motion estimation becomes more stable and the spacing of high-resolution pixels on the rectified module image becomes uniform w.r.t. the module plane, regardless of perspective distortion. We present a comprehensive user study showing that MFSR is beneficial for defect recognition by human experts and that the proposed method performs better than the state-of-the-art. Furthermore, we apply automated crack segmentation and show that the proposed method performs 3× better than bicubic upsampling and 2× better than the state-of-the-art for automated inspection