An　image　reconstruction　algorithm　is　vital　for　the　image　quality　of　a　photonic　integrated　interferometric　imaging　(PIII)　system.　However,　image　reconstruction　algorithms　have　limitations　that　always　lead　to　degraded　image　reconstruction.　In　this　paper,　a　novel　image　reconstruction　algorithm　based　on　deep　learning　is　proposed.　Firstly,　the　principle　of　optical　signal　transmission　through　the　PIII　system　is　investigated.　A　dataset　suitable　for　image　reconstruction　of　the　PIII　system　is　constructed.　Key　aspects　such　as　model　and　loss　functions　are　compared　and　constructed　to　solve　the　problem　of　image　blurring　and　noise　influence.　By　comparing　it　with　other　algorithms,　the　proposed　algorithm　is　verified　to　have　good　reconstruction　results　not　only　qualitatively　but　also　quantitatively.