Search Results for author: Kivanc Kose

Found 6 papers, 0 papers with code

Segmentation of Cellular Patterns in Confocal Images of Melanocytic Lesions in vivo via a Multiscale Encoder-Decoder Network (MED-Net)

no code implementations3 Jan 2020 Kivanc Kose, Alican Bozkurt, Christi Alessi-Fox, Melissa Gill, Caterina Longo, Giovanni Pellacani, Jennifer Dy, Dana H. Brooks, Milind Rajadhyaksha

We trained and tested our model on non-overlapping partitions of 117 reflectance confocal microscopy (RCM) mosaics of melanocytic lesions, an extensive dataset for this application, collected at four clinics in the US, and two in Italy.

Segmentation Semantic Segmentation +1

A Multiresolution Convolutional Neural Network with Partial Label Training for Annotating Reflectance Confocal Microscopy Images of Skin

no code implementations5 Feb 2018 Alican Bozkurt, Kivanc Kose, Christi Alessi-Fox, Melissa Gill, Dana H. Brooks, Jennifer G. Dy, Milind Rajadhyaksha

We describe a new multiresolution "nested encoder-decoder" convolutional network architecture and use it to annotate morphological patterns in reflectance confocal microscopy (RCM) images of human skin for aiding cancer diagnosis.

Specificity

Delineation of Skin Strata in Reflectance Confocal Microscopy Images using Recurrent Convolutional Networks with Toeplitz Attention

no code implementations1 Dec 2017 Alican Bozkurt, Kivanc Kose, Jaume Coll-Font, Christi Alessi-Fox, Dana H. Brooks, Jennifer G. Dy, Milind Rajadhyaksha

Reflectance confocal microscopy (RCM) is an effective, non-invasive pre-screening tool for skin cancer diagnosis, but it requires extensive training and experience to assess accurately.

General Classification

Signal Reconstruction Framework Based On Projections Onto Epigraph Set Of A Convex Cost Function (PESC)

no code implementations10 Feb 2014 Mohammad Tofighi, Kivanc Kose, A. Enis Cetin

A new signal processing framework based on making orthogonal Projections onto the Epigraph Set of a Convex cost function (PESC) is developed.

Compressive Sensing Denoising

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