In　this　paper,　we　explored　the　feasibility　of　using　ultrasound　Nakagami-m　parametric　imaging　based　on　Gaussian　pyramid　decomposition　(GPD)　to　detect　microwave　ablation　coagulation　areas.　Monte　Carlo　simulation　and　phantom　simulation　results　demonstrated　that　a　2-layer　GPD　model　was　sufficient　to　achieve　the　same　m　parameter　estimation　accuracy,　smoothness　and　resolution　as　3-layer　and　4-layer.　The　performances　of　GPD,　moment-based　estimator　(MBE)　and　window-modulated　compounding　(WMC)　algorithms　were　compared　in　terms　of　parameter　estimation,　smoothness,　resolution　and　contrast-to-noise　(CNR).　Results　showed　that　the　m　parameter　estimation　obtained　by　GPD　algorithm　was　better　than　that　of　MBE　and　WMC　algorithms　except　the　small　window　size　(27　x　5).　When　using　a　window　size　of　＞　3　pulse　lengths,　GPD　algorithm　could　achieve　better　smoothness　and　CNR　than　MBE　and　WMC　algorithms,　but　there　was　a　certain　loss　of　axial　resolution.　The　computation　time　of　GPD　algorithm　was　less　than　that　of　WMC　algorithm,　while　about　2.24　times　that　of　MBE　algorithm.　Experimental　results　of　porcine　liver　microwave　ablation　ex　vivo　(n　=　20)　illustrated　that　the　average　areas　under　the　operating　characteristic　curve　(AUCs)　of　Nakagami　mGPD,　mMBE　and　mWMC　parametric　imaging　and　homodyned-K　(HK)　a　and　k　parametric　imaging　to　detect　coagulation　areas　were　significantly　improved　by　polynomial　approximation　(PAX).　Kruskal-Wallis　test　showed　that　the　accuracy　of　coagulation　area　detection　obtained　by　PAX　imaging　of　mGPD　parameter　had　no　significant　difference　with　that　of　mMBE,　mWMC,　HK_a　and　HK_k　parameters.　This　preliminary　study　suggested　that　Nakagami　imaging　based　on　GPD　algorithm　may　have　the　potential　to　detect　microwave　ablation　coagulation　areas.