The　homodyned-K　(HK)　distribution　is　a　generalized　model　of　envelope　statistics　whose　parameters　alpha　(the　clustering　parameter)　and　k　(the　coherent-to-diffuse　signal　ratio)　can　be　used　to　monitor　the　thermal　lesions.　In　this　study,　we　proposed　an　ultrasound　HK　contrast-weighted　summation　(CWS)　parametric　imaging　algorithm　based　on　the　H-scan　technique　and　investigated　the　optimal　window　side　length　(WSL)　of　the　HK　parameters　estimated　by　the　XU　estimator　(an　estimation　method　based　on　the　first　moment　of　the　intensity　and　two　log-moments,　which　was　used　in　the　proposed　algorithm)　through　phantom　simulations.　H-scan　diversified　ultrasonic　backscattered　signals　into　low-　and　high-frequency　passbands.　After　envelope　detection　and　HK　parameter　estimation　for　each　frequency　band,　the　alpha　and　k　parametric　maps　were　obtained,　respectively.　According　to　the　contrast　between　the　target　region　and　background,　the　(alpha　or　k)　parametric　maps　of　the　dual-frequency　band　were　weighted　and　summed,　and　then　the　CWS　images　were　yielded　by　pseudo-color　imaging.　The　proposed　HK　CWS　parametric　imaging　algorithm　was　used　to　detect　the　microwave　ablation　coagulation　zones　of　porcine　liver　ex　vivo　under　different　powers　and　treatment　durations.　The　performance　of　the　proposed　algorithm　was　compared　with　that　of　the　conventional　HK　parametric　imaging　and　frequency　diversity　and　compounding　Nakagami　imaging　algorithms.　For　two-dimensional　HK　parametric　imaging,　it　was　found　that　a　WSL　equal　to　4　pulse　lengths　of　the　transducer　was　sufficient　for　estimating　the　alpha　and　k　parameters　in　terms　of　both　parameter　estimation　stability　and　parametric　imaging　resolution.　The　HK　CWS　parametric　imaging　provided　an　improved　contrast-to-noise　ratio　over　conventional　HK　parametric　imaging,　and　the　HK　alpha(cws)　parametric　imaging　achieved　the　best　accuracy　and　Dice　score　of　coagulation　zone　detection.