Daniel Racoceanu

Learn More
INTRODUCTION In the framework of the Cognitive Microscope (MICO) project, we have set up a contest about mitosis detection in images of H and E stained slides of breast cancer for the conference ICPR 2012. Mitotic count is an important parameter for the prognosis of breast cancer. However, mitosis detection in digital histopathology is a challenging problem(More)
Colorectal adenocarcinoma originating in intestinal glandular structures is the most common form of colon cancer. In clinical practice, the morphology of intestinal glands, including architectural appearance and glandular formation, is used by pathologists to inform prognosis and plan the treatment of individual patients. However, achieving good(More)
Digital pathology represents one of the major evolutions in modern medicine. Pathological examinations constitute the gold standard in many medical protocols, and also play a critical and legal role in the diagnosis process. In the conventional cancer diagnosis, pathologists analyze biopsies to make diagnostic and prognostic assessments, mainly based on the(More)
In this paper, we propose a unitary tool for modeling and analysis of discrete event systems monitoring. Uncertain knowledge of such tasks asks specific reasoning and adapted fuzzy logic modeling and analysis methods. In this context, we propose a new fuzzy Petri net called Fuzzy Reasoning Petri Net: the FRPN. The modeling consists in a set of two(More)
CONTEXT According to Nottingham grading system, mitosis count in breast cancer histopathology is one of three components required for cancer grading and prognosis. Manual counting of mitosis is tedious and subject to considerable inter- and intra-reader variations. AIMS The aim is to investigate the various texture features and Hierarchical Model and X(More)
This paper presents the contribution of IPAL group on the CLEF 2006 medical retrieval task (i.e. ImageCLEFmed). The main idea of our group is to incorporate medical knowledge in the retrieval system within a multimodal fusion framework. For text, this knowledge is in the Unified Medical Language System (UMLS) sources. For images, this knowledge is in(More)
Breast cancer grading of histopathological images is the standard clinical practice for the diagnosis and prognosis of breast cancer development. In a large hospital, a pathologist typically handles 100 grading cases per day, each consisting of about 2000 image frames. It is, therefore, a very tedious and time-consuming task. This paper proposes a method(More)
Scoring the nuclear pleomorphism in histopathological images is a standard clinical practice for the diagnosis and prognosis of breast cancer. It relies highly on the experience of the pathologists. In a large hospital, one pathologist may have to evaluate more than a hundred cases per day, which is a very tedious and time-consuming task. Thus, it is(More)
OBJECTIVE We investigate the influence of the clinical context of high-resolution computed tomography (HRCT) images of the chest on tissue classification. METHODS AND MATERIALS 2D regions of interest in HRCT axial slices from patients affected with an interstitial lung disease are automatically classified into five classes of lung tissue. Relevance of the(More)
Histopathological examination is a powerful standard for the prognosis of critical diseases. But, despite significant advances in high-speed and high-resolution scanning devices or in virtual exploration capabilities, the clinical analysis of whole slide images (WSI) largely remains the work of human experts. We propose an innovative platform in which(More)