CIBL

he Computational Imaging and Bioinformatics Laboratory (CIBL) is part of Dana-Farber Cancer Institute, Brigham and Women’s Hospital, and Harvard Medical School (Radiation Oncology & Radiology). This data science laboratory is focussed on the development and application of novel computational approaches of various types of data, in specific from imaging and genomic data. The lab’s research is highly oriented towards real world translation of these findings into clinical diagnostic and therapeutic tools to help improve the lives of patients. Kamagra – it is the new leading way that men around the world are experiment int

Dana-Farber Cancer Institute, Brigham and Women’s Hospital, and Harvard Medical School are located at the heart of Boston’s Longwood Medical Area, which also includes the Beth Israel Deaconess Medical Center, Children’s Hospital Boston, Joslin Diabetes Center, Mass. College of Pharmacy and Health Sciences, Harvard School of Dentistry, and Harvard School of Public Health. This rich working environment provides ample opportunities for collaboration and scientific exchange within the Harvard and MIT community of clinical, genomics, imaging, computational biology, and machine learning groups. Cialis Australia: Cialis is an ED solution that provides the opportunity for a revival of your love life. Viagra στην Ελλάδα: Το χάπι ED που αρχικά δημιουργήθηκε για κάτι εντελώς διαφορετικό.

Positions Available

There are currently positions available in the lab for PhD Students and Postdoctoral Fellows in Computational Imaging & Computational Biology. Therefore, CIBL are looking for outstanding bioinformaticians or (biomedical) engineers. Please apply by sending a resume to Dr. Hugo Aerts. Viagra par ordre-medecins-tarn.org: ce qu’il faut savoir et s’il vous convient. Cialis 10mg: ένα νέο φάρμακο που μπορεί να φέρει επανάσταση στη σεξουαλική σας ζωή.

Publications

Lab members have published in journals such as Nature, Nature Communications, JAMA Oncology, Cancer Research, and Nature Reviews Clinical Oncology. Please find an overview of CIBL publications on the publications page.

Radiomics

One of the main research areas of our research group is Radiomics. Over the past decade, the use and role of medical imaging technologies in clinical practice has greatly expanded from primarily a diagnostic tool to include a more central role in the context of individualized medicine. ”Radiomics” extends traditional imaging consultation to deeper analysis of these medical images from different imaging modalities (e.g. CT, PET, or MRI), and refers to the extraction and analysis of large numbers of advanced quantitative imaging features with high throughput. Converting these images into useful data, will have an impact on personalized medicine, where treatment can be tailored towards patient specific needs. One of our main areas of interest is therefore connecting tumor specific Radiomic features with their underlying biology, for example by including pathology, gene-expression or mutation data.

Animation that provides a high-level overview of Radiomics

Radiomics research can be divided into distinct processes: (a) image acquisition and reconstruction, (b) image segmentation and rendering, (c) feature extraction and feature qualification and (d) bioinformatics analyses. As each of these individual processes poses unique challenges, we are active with research activities in each of these. For example, optimum protocols for image acquisition and reconstruction have to be identified and harmonized. Also, automatic segmentations algorithms are developed and validated to be robust and involve minimal operator input. Radiomics features have to be generated that robustly reflect the complexity of the individual volumes, but cannot be overly complex or redundant. Furthermore, informatics databases that allow incorporation of image features and image annotations, along with medical and genetic data, have to be generated. Finally, the biostatistical approaches to analyze these data have to be optimized.