Younger Age is an Independent Factor for Graft Weight Overestimation: Analysis of the Clinical Impact on Recipient Outcomes in 340 Japanese Living Liver Donors.

Background: Accurate preoperative estimation of graft weight is essential for improving outcomes in living donor liver transplantation.

Methods: This retrospective study sought to identify factors associated with graft weight overestimation. From April 2006 to August 2015, 340 living donors were assigned to no-overestimate (n = 284) or overestimate (n = 56) groups.

LECANDUS study (LEsion CANdidate Detection in UltraSound Data): evaluation of image analysis algorithms for breast lesion detection in volume ultrasound data.

Purpose: This study aims at developing and evaluating a prototype of a lesion candidate detection algorithm for a 3D-US computer-aided diagnosis (CAD) system.

Methods: Additionally, to routine imaging, automated breast volume scans (ABVS) were performed on 63 patients. All ABVS exams were analyzed and annotated before the evaluation with different algorithm blob detectors characterized by different blob-radiuses, voxel-sizes and the quantiles of blob filter responses to find lesion candidates.

Principles and methods for automatic and semi-automatic tissue segmentation in MRI data.

The development of magnetic resonance imaging (MRI) revolutionized both the medical and scientific worlds. A large variety of MRI options have generated a huge amount of image data to interpret. The investigation of a specific tissue in 3D or 4D MR images can be facilitated by image processing techniques, such as segmentation and registration.

On the evaluation of segmentation editing tools.

Efficient segmentation editing tools are important components in the segmentation process, as no automatic methods exist that always generate sufficient results. Evaluating segmentation editing algorithms is challenging, because their quality depends on the user's subjective impression. So far, no established methods for an objective, comprehensive evaluation of such tools exist and, particularly, intermediate segmentation results are not taken into account.

Comparison of volumetric and linear serial CT assessments of lung metastases in renal cell carcinoma patients in a clinical phase IIB study.

Rationale And Objectives: Accuracy of radiologic assessment may have a crucial impact on clinical studies and therapeutic decisions. We compared the variability of a central radiologic assessment (RECIST) and computer-aided volume-based assessment of lung lesions in patients with metastatic renal cell carcinoma (RCC).

Materials And Methods: The investigation was prospectively planned as a substudy of a clinical randomized phase IIB therapeutic trial in patients with RCC.

Pulmonary lymphangioleiomyomatosis: analysis of disease manifestation by region-based quantification of lung parenchyma.

Purpose: Lymphangioleiomyomatosis (LAM) is characterized by proliferation of smooth muscle tissue that causes bronchial obstruction and secondary cystic destruction of lung parenchyma. The aim of this study was to evaluate the typical distribution of cystic defects in LAM with quantitative volumetric chest computed tomography (CT).

Materials And Methods: CT examinations of 20 patients with confirmed LAM were evaluated with region-based quantification of lung parenchyma.

Robust semi-automatic segmentation of pulmonary subsolid nodules in chest computed tomography scans.

The malignancy of lung nodules is most often detected by analyzing changes of the nodule diameter in follow-up scans. A recent study showed that comparing the volume or the mass of a nodule over time is much more significant than comparing the diameter. Since the survival rate is higher when the disease is still in an early stage it is important to detect the growth rate as soon as possible.

Visualization support for the planning of hepatic needle placement.

Purpose: Percutaneous image-guided interventions, such as radiofrequency ablation or biopsy, are using needle-shaped instruments which have to be inserted into a target area without penetrating any vital structure. The established planning workflow is based on viewing 2D slices of a pre-interventional CT or MR scan. However, access paths not parallel to the axial plane are often necessary.

Object-based analysis of CT images for automatic detection and segmentation of hypodense liver lesions.

Purpose: Hypodense liver lesions are commonly detected in CT, so their segmentation and characterization are essential for diagnosis and treatment. Methods for automatic detection and segmentation of liver lesions were developed to support this task.

Methods: The detection algorithm uses an object-based image analysis approach, allowing for effectively integrating domain knowledge and reasoning processes into the detection logic.

A robust and extendible framework for medical image registration focused on rapid clinical application deployment.

Development and integration of image registration methods become increasingly important for clinical workstations. Due to the complexity of such methods, prototyping, evaluation and workflow integration require in-depth knowledge foremostly available to registration developers. Rapid development and deployment is therefore often difficult, particularly for comprehensive software frameworks.

Computer assistance for MR based diagnosis of breast cancer: present and future challenges.

MR based methods have gained an important role for the clinical detection and diagnosis of breast cancer. Dynamic contrast-enhanced MRI of the breast has become a robust and successful method, especially for diagnosis of high-risk cases due to its higher sensitivity compared to X-ray mammography. The application of MR based imaging methods depends on various automated image processing routines.

Morphological segmentation and partial volume analysis for volumetry of solid pulmonary lesions in thoracic CT scans.

Volumetric growth assessment of pulmonary lesions is crucial to both lung cancer screening and oncological therapy monitoring. While several methods for small pulmonary nodules have previously been presented, the segmentation of larger tumors that appear frequently in oncological patients and are more likely to be complexly interconnected with lung morphology has not yet received much attention. We present a fast, automated segmentation method that is based on morphological processing and is suitable for both small and large lesions.

Informatics in radiology (infoRAD): new tools for computer assistance in thoracic CT part 2. Therapy monitoring of pulmonary metastases.

Owing to the rapid development of scanner technology, thoracic computed tomography (CT) offers new possibilities but also faces enormous challenges with respect to the quality of computer-assisted diagnosis and therapy planning. In the framework of the Virtual Institute for Computer Assistance in Clinical Radiology cooperative research project, a software application was developed to assist the radiologist in the analysis of thoracic CT data for the purpose of evaluating the response to tumor therapy. The application provides follow-up support for monitoring of tumor therapy by means of volumetric quantification of tumors and temporal registration.

Informatics in radiology (infoRAD): new tools for computer assistance in thoracic CT. Part 1. Functional analysis of lungs, lung lobes, and bronchopulmonary segments.

Owing to the rapid development of scanner technology, thoracic computed tomography (CT) offers new possibilities but also faces enormous challenges with respect to the quality of computer-assisted diagnosis and therapy planning. In the framework of the Virtual Institute for Computer Assistance in Clinical Radiology cooperative research project, a prototypical software application was developed to assist the radiologist in functional analysis of thoracic CT data. By identifying the anatomic compartments of the lungs, the software application enables assessment of established functional CT parameters for each individual lung, pulmonary lobe, and pulmonary segment.

Evaluation of accuracy in MS lesion volumetry using realistic lesion phantoms.

Rationale And Objectives: Quantitative analysis of such small structures as focal lesions in patients with multiple sclerosis (MS) is an important issue in both diagnosis and therapy monitoring. To reach clinical relevance, the reproducibility and accuracy of a proposed method have to be validated. We propose a framework for the generation of realistic digital phantoms of MS lesions of known volumes and their incorporation into a magnetic resonance (MR) data set of a healthy volunteer.

Highly specific prediction of phosphorylation sites in proteins.

Summary: The prediction of significant short functional protein sequences has inherent problems. In predicting phosphorylation sites, problems came from the shortness of phosphorylation sites, the difficulties in maintaining many different predefined models of binding sites, and the difficulties of obtaining highly sensitive predictions and of obtaining predictions with a constant sensitivity and specificity. The algorithm presented in this paper overcomes these problems.