Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:   present a boosting based approach for automatic detection of micro-calcifications in mammographic images Our proposal is based on using local features extracted from a bank of filters for obtaining a description of the different micro-calcifications morphology The approach performs an initial training step in order to automatically learn and select the most salient features, which are subsequently used in a boosting classifier to perform the detection The validity of our method is demonstrated using 112 mammograms of the ll-known digitised MIAS database and 280 mammograms of a full-field digital database The experimental evaluation is performed in terms of ROC analysis, obtaining Az=0.88 and Az=0.90 respectively, and FROC analysis The obtained results show the feasibility of our approach for detecting micro-calcifications in both digitised and digital technologies.
['Arnau Oliver', 'Albert Torrent', 'Meritxell Tortajada', 'Xavier Lladó', 'Marta Peracaula', 'Lidia Tortajada', 'Melcior Sentís', 'Jordi Freixenet']
I am writing a research paper on a idea A boosting based approach for automatic micro-calcification detection
[{"from": "human", "value": "I am writing a research paper on a idea A boosting based approach for automatic micro-calcification detection"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:   present a boosting based approach for automatic detection of micro-calcifications in mammographic images Our proposal is based on using local features extracted from a bank of filters for obtaining a description of the different micro-calcifications morphology The approach performs an initial training step in order to automatically learn and select the most salient features, which are subsequently used in a boosting classifier to perform the detection The validity of our method is demonstrated using 112 mammograms of the ll-known digitised MIAS database and 280 mammograms of a full-field digital database The experimental evaluation is performed in terms of ROC analysis, obtaining Az=0.88 and Az=0.90 respectively, and FROC analysis The obtained results show the feasibility of our approach for detecting micro-calcifications in both digitised and digital technologies."}]