In　order　to　decrease　the　dependency　of　the　conventional　segmentation　algorithms　on　initial　conditions,　a　medical　image　segmentation　framework　based　on　an　adaptive　region　is　presented.　The　framework　integrates　the　segmentation　and　object　detection　techniques　into　a　pipeline,　and　the　local　region　of　objects　in　the　slice　to　be　segmented　is　determined　according　to　the　detection　results　of　the　segmented　slice.　Based　on　this　region,　the　threshold　and　geometric　shape　parameters　can　be　obtained　and　used　to　the　successive　segmentation.　This　framework　has　been　applied　to　region　growing　and　threshold-based　level　set　algorithms　to　segment　lots　of　slice　images.　The　experimental　results　show　that　the　proposed　framework　can　effectively　decrease　manual　interaction,　and　well　handle　the　complicated　bifurcations　of　objects.