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Journal  Conference  Conference  Journal  Journal  Journal  Journal  Journal  Conference  Continued






                    [88]   [89]      [90]  [91]    [92]    [93]        [94]     [95]   [96]
                    consisted  retinopathy  9653  11,347  the  and  used  eye,  per  images  which  used,  images  set  data  patient's  the  on  (BCDR)  randomly  taken  taken  was


                    used      of  and  DRIVE  was  color  image  1748  was  850  cancer  film  736  available  was  archive,  Center,  segmented  was  set

                    was  images  diabetic  consisted  the  that  retinal  diabetes,  set  BI-RADS  benchmarking  of  Repository  MRIs  Medical  views  data  purpose
                    that   a    images  were  set  digital  fovea-centered  data  approximately  of  breast  total  was  scientific  Netherlands  manually  INbreast
                    set  fundus  from  initiative  retinal  used  data  the  with  terms  344  a  that  Digital  breast  the  University  40  oblique
                    data  patient  acquired  images  sets  Messidor-2  of  one  subjects  hospital  of  in  biopsy-proven  from  containing  Cancer  66  of  from  The  with  available  experimental

                    DRISHTI-GS  50  of  set  Data  screening  ungradable  gradable  data  Two  STARE  The  consisted  images,  874  of  Multicenter  consisted  distributed  new  A  built  was  cases  mammography  Breast  set  data  A  selected  Radboud  Nijmegen,  set  data  A  mediolateral  Publicly  the  for





                    fundus  imaging  image  image  retinal  images  Mammography  Mammography  Mammography  Mammography

                    Color  Retinal   Fundus  Digital  color            MRI

                    Ensemble-based  CNN  five  with  CNN  convolution  named  layers  CNN5  as  FCNN  CNN  Faster-R-CNN  and  CNN2  CNN3  U-Net  CNN





                    optic  as  of    of            and     of          of       framework
                    automated  well  as  assessment  segmentation  diabetic  classification  breast  diagnosis  representation  segmentation  tissue  a  into  tissues  breast  malignant



                    the  glaucoma  the  quality  improved  of  in  the  for  for  fibroglandular  create  coherent  classify  or
                    for  segmentation  for  for  vessel  for  detection  for  tumors  using  framework  to  classification  to  benign
                    designed  disc  of  developed  image  developed  retinal  designed  automated  retinopathy  designed  of  mammograms  developed  cancer  developed  and  designed  region  semantically  designed  as


                    Model  cup,  detection  Model  retinal  Model  the  Model  System  detection  System  breast  learning  System  breast  System  for  Model  masses

                                                   2016

                                                   Breast
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