DoctorEye: A multifunctional open platform for fast annotation and visualization of tumors in medical images

Ratsnake: a versatile image annotation tool with application to computer-aided diagnosis

Image segmentation and annotation are key components of image-based medical computer-aided diagnosis (CAD) systems. In this paper we present Ratsnake, a publicly available generic image annotation tool providing annotation efficiency, semantic awareness, versatility, and extensibility, features that can be exploited to transform it into an effective CAD system. In order to demonstrate this unique capability, we present its novel application for the evaluation and quantification of salient objects and structures of interest in kidney biopsy images. Accurate annotation identifying and quantifying such structures in microscopy images can provide an estimation of pathogenesis in obstructive nephropathy, which is a rather common disease with severe implication in children and infants. However a tool for detecting and quantifying the disease is not yet available. A machine learning-based approach, which utilizes prior domain knowledge and textural image features, is considered for the generation of an image force field customizing the presented tool for automatic evaluation of kidney biopsy images. The experimental evaluation of the proposed application of Ratsnake demonstrates its efficiency and effectiveness and promises its wide applicability across a variety of medical imaging domains.

A software prototype for the assessment of tumor treatment response using diffusion and perfusion MR imaging

Advanced MRI techniques including diffusion and perfusion weighted imaging, has the potential to provide early surrogate biomarkers to detect, characterize and assess treatment response of tumors. However, the widely accepted Response Evaluation Criteria in Solid Tumors (RECIST) are still considered as the gold standard for the evaluation of treatment response in solid tumors, even if according to recent studies RECIST seem to disregard the extent of necrosis, which is the target of all effective locoregional therapies. This is partly due to the fact that measurements of tumor size aren't the best criterion for assessing actual early response. On the other hand, more sophisticated techniques such as the Apparent Diffusion Coefficient (ADC) and perfusion parameters are usually processed manually and evaluated independently using commercial CAD software, not widely available. In this paper we present an open access extensible software platform providing both diffusion and perfusion analysis in a single, user friendly environment that allows the radiologist to easily and objectively evaluate tumor response to therapy.

Evaluation framework for the multilevel macroscopic models of solid tumor growth in the glioma case

This paper investigates the applicability of multilevel macroscopic models for simulating solid tumor growth in the invasive glioblastoma multiforme (GBM) case. The continuum case approach tumor model based on the diffusion reaction equation is evaluated on a pre-segmented tomographic atlas where all tissue properties are known a priori. The atlas is further registered on a real clinical case where the tumor invasion status is gauged in two successive points in time. Based on the latter, the model attempts to fully replicate tumor growth taking into account tissue based properties as identified from the atlas template. The whole process is performed on a clinical platform specially designed to facilitate precise identification and delineation of tumors of large number of 3D tomographic datasets by an expert clinician. The promising results presented encourage the potential clinical applicability of the proposed model in the glioma case and identify crucial points and direction of further model refinement and research.