In　order　to　make　regions　appearing　as　dots　on　a　chest　radiograph　more　clearly　in　visual,　a　novel　filtering　method,　Hessian-LoG　filter.　is　developed　in　this　paper.　The　proposed　filter　consists　of　two　major　operations.　First,　using　the　eigenvalues　of　Hessian　matrix　detects　dot　points　in　chest　radiography.　The　derivatives　of　a　Hessian　matrix　at　multiple　scales　are　convolved　with　an　input　image　at　each　pixel.　To　determine　the　local　shape　of　structures　at　pixels　in　each　scale,　the　eigenvalues　of　Hessian　matrix　are　analyzed　at　each　pixel　in　the　resulting　image.　The　diameter　of　the　detected　dot　is　equal　to　the　kernel　size　with　the　highest　classifier　value.　Finally,　dot　images　are　convolved　with　the　Laplacian　of　Gaussian　(LoG)　operator.　Experiments　show　that　the　proposed　enhancement　filter　can　simultaneously　enhance　dot-like　objects　and　suppress　line-like　structures,　and　thus　improve　the　sensitivity　of　nodule　detection.　©　2012　ICIC　International.