Projects

Mitosis detection in digital pathology

• • 6th place CCIPD/MINDLAB in the AMIDA Grand Challenge, part of MICCAI'2013

  • SPIE'2014 paper: 2nd place (offline) in the ICPR'2012 Mitosis Challenge

  • JMI'2014: Mitosis detection in breast cancer pathology images by combining handcrafted and convolutional neural network features (Journal) [URL]

Unsupervised and supervised feature learning in digital pathology

• • SPIE'2014: Invasive ductal carcinoma BCa detection with Convoloutional Neural Networks

  • SIPAIM'2013: Unsupervised feature learning (Sparse Autoencoders and Topographic ICA) for Basal cell carcinoma detection

  • MICCAI'2013: Basal cell carcinoma classification and digital staining via Sparse Autoencoders (Student Travel Award)

Bag of Features in digital pathology

• • SIPAIM'2013: Bag of Visual N-grams for Basal cell carcinoma classification

  • SPIE'2013: Sparse dictionary learning and Bag of Features for Cervix cancer detection

  • SIPAIM'2012: Predicting morphometric measures from a Bag of Features representation in Cervix cancer cells

  • MICCAI'2012: Interpretable visual latent semantic model with Bag of Features in Medulloblastoma tumor differentiation

  • AIM'2011: Visual pattern mining in histology and histopathology image collections using Bag of features (Journal)

  • JPI'2012: Automatic annotation in Basal cell carcinoma images by latent topic model with non-negative matrix factorization and Bag of Features (Journal)

  • MICCAI'2011: Automatic annotation in Basal cell carcinoma images by latent topic model with non-negative matrix factorization and Bag of Features (HIMA Workshop)

  • 6CCC (2011): Semantic analysis of Basal cell carcinoma images using Bag of Features and Convex Non-Negative Matrix Factorization

  • SIPAIM'2010: Visual mining in histopathology images using Bag of features

  • AIME'2009: Bag of features and Kernel methods for Basal cell carcinoma image annotation

  • CIARP'2009: Bag of features and correlation analysis for visual pattern analysis in Basal cell carcinoma images

High-performance computing for image analysis

• • BIGS - Big Image Data Analysis Toolkit (HPC framework tool)

  • IEEE-eScience'2012: Framework for mage processing and analysis over heterogenous computing resources (Amazon Web Services and Local Intranet).

  • CLCAR'2012: Framework for image feature extraction over Cloud resources

  • 7CCC (2012): Framework for high performance image analysis pipelines

Content-based image retrieval for histopathology image databases

• • BiMed - Content-Based Retrieval in a Histology Image Database (Online Histology Atlas of 20,000 images)

  • e-Colabora'2012: System for storage, semantic retrieval and automatic annotation of histology images by Grid infrastructures and RENATA network

  • Acta Biológica Colombiana (2010): A System for Accessing a Collection of Biomedical Images Using Content-Based Strategies (Journal)

  • eScience'2009: Web-Based System for Biomedical Image Storage, Annotation, Content-Based Retrieval and Exploratio

  • SIPAIM'2009: Visual content-based image retrieval based on global features

  • e-Colabora'2008: System for medical content-based image retrieval

Sperm analysis in veterinary informatics

• • CIASEM'2013: Automatic quantification of sperm movility in fish by tracking analysis in videos

  • 2CCC (2007): Expert system for sperm morphology classification and aided diagnosis

  • 2CCBIB (2005): Morphology classification of spermatozoa via morphological features and artificial neural networks (Best oral presentation in biomedical signal and image processing modality)

Image analysis and machine learning in Radiology Imaging

• • SIPAIM'2012: A comprenhesive feature analysis for modality classification of medical images (ImageCLEFmed dataset)

  • SIPAIM'2011: Multi-label annotation or radiological images using visual latent semantic models

  • CIARP'2012: Spatio-visual Bag of Features for Alzheimer's disease classification in structural MRI

  • 4CCC (2009): Transductive Support Vector Machines for X-Ray image classification

Cell Mophology via image processing and machine learning

• • CNCB'2013: Neural morphology analysis for healthy and pathological brains

  • CIASEM'2013: Structural alterations of neurons caused by rabies virus via morphometric analysis

  • AsocColombDermatol (2009): Melanocytes quantification in face skin to aid resection edges of melanoma lesions (Journal)

  • LACNEM'2009: (spanish) Automatic Karyotype analysis in Bovine via image processing and pattern recognition

  • 3CCBIB (2008): Automatic Cysts detection of Giardia duodenalis by multichannel segmentation, k-means clustering and decision tree