ImageDimPlot() not plotting molecules on specific fovs created by Crop function

[elifozcelik]

Hi, when I use ImageDimPlot function with my initial slides, I can see the molecules. However when I create a fov using Crop function, I can see the cropped image but there is no molecules mapped. How can I solve this issue? I use the following code to plot both of them:

ImageDimPlot(cancer, fov = "C16_fov2", alpha = 0.3, molecules = "KRT17")

Thank you

sessionInfo()
R version 4.3.3 (2024-02-29)
Platform: x86_64-conda-linux-gnu (64-bit)
Running under: Rocky Linux 8.7 (Green Obsidian)

Matrix products: default
BLAS/LAPACK: /home/fs01/elo4010/.conda/envs/spatial_env/lib/libopenblasp-r0.3.21.so; LAPACK version 3.9.0

locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C

time zone: America/New_York
tzcode source: system (glibc)

attached base packages:
[1] grid stats graphics grDevices utils datasets methods
[8] base

other attached packages:
[1] circlize_0.4.16 ComplexHeatmap_2.18.0 dittoSeq_1.14.3
[4] InSituType_2.0 dplyr_1.1.3 ggplot2_3.5.1
[7] Seurat_5.1.0 SeuratObject_5.0.2 sp_2.1-1

loaded via a namespace (and not attached):
[1] RcppAnnoy_0.0.21 splines_4.3.3
[3] later_1.3.1 bitops_1.0-7
[5] tibble_3.2.1 polyclip_1.10-6
[7] fastDummies_1.7.3 lifecycle_1.0.3
[9] doParallel_1.0.17 globals_0.16.2
[11] lattice_0.22-5 MASS_7.3-60
[13] SnowballC_0.7.1 magrittr_2.0.3
[15] plotly_4.10.2 httpuv_1.6.15
[17] sctransform_0.4.1 spam_2.9-1
[19] askpass_1.2.0 spatstat.sparse_3.0-2
[21] reticulate_1.39.0 cowplot_1.1.1
[23] pbapply_1.7-2 RColorBrewer_1.1-3
[25] abind_1.4-5 zlibbioc_1.48.0
[27] Rtsne_0.16 GenomicRanges_1.54.1
[29] purrr_1.0.2 BiocGenerics_0.48.1
[31] RCurl_1.98-1.12 GenomeInfoDbData_1.2.11
[33] IRanges_2.36.0 S4Vectors_0.40.2
[35] ggrepel_0.9.4 irlba_2.3.5.1
[37] listenv_0.9.0 spatstat.utils_3.0-3
[39] pheatmap_1.0.12 umap_0.2.10.0
[41] goftest_1.2-3 RSpectra_0.16-1
[43] spatstat.random_3.1-6 fitdistrplus_1.1-11
[45] parallelly_1.36.0 leiden_0.4.3
[47] codetools_0.2-19 DelayedArray_0.28.0
[49] tidyselect_1.2.0 shape_1.4.6.1
[51] farver_2.1.1 matrixStats_1.0.0
[53] stats4_4.3.3 spatstat.explore_3.2-3
[55] jsonlite_1.8.7 GetoptLong_1.0.5
[57] ellipsis_0.3.2 progressr_0.14.0
[59] ggridges_0.5.4 survival_3.5-7
[61] iterators_1.0.14 systemfonts_1.0.5
[63] foreach_1.5.2 tools_4.3.3
[65] ica_1.0-3 Rcpp_1.0.11
[67] glue_1.6.2 gridExtra_2.3
[69] SparseArray_1.2.2 MatrixGenerics_1.14.0
[71] GenomeInfoDb_1.38.1 withr_2.5.1
[73] fastmap_1.1.1 fansi_1.0.5
[75] openssl_2.1.1 digest_0.6.33
[77] R6_2.5.1 mime_0.12
[79] textshaping_0.3.7 colorspace_2.1-0
[81] scattermore_1.2 tensor_1.5
[83] spatstat.data_3.0-1 utf8_1.2.4
[85] tidyr_1.3.0 generics_0.1.3
[87] data.table_1.15.4 httr_1.4.7
[89] htmlwidgets_1.6.2 S4Arrays_1.2.0
[91] uwot_0.1.16 pkgconfig_2.0.3
[93] gtable_0.3.4 lmtest_0.9-40
[95] SingleCellExperiment_1.24.0 XVector_0.42.0
[97] htmltools_0.5.6.1 dotCall64_1.1-0
[99] clue_0.3-65 scales_1.3.0
[101] Biobase_2.62.0 png_0.1-8
[103] reshape2_1.4.4 rjson_0.2.23
[105] nlme_3.1-163 zoo_1.8-12
[107] GlobalOptions_0.1.2 stringr_1.5.0
[109] KernSmooth_2.23-22 parallel_4.3.3
[111] miniUI_0.1.1.1 pillar_1.9.0
[113] vctrs_0.6.4 RANN_2.6.1
[115] lsa_0.73.3 promises_1.2.1
[117] xtable_1.8-4 cluster_2.1.4
[119] cli_3.6.1 compiler_4.3.3
[121] rlang_1.1.1 crayon_1.5.2
[123] future.apply_1.11.0 labeling_0.4.3
[125] mclust_6.1.1 plyr_1.8.9
[127] stringi_1.7.12 viridisLite_0.4.2
[129] deldir_1.0-9 munsell_0.5.0
[131] lazyeval_0.2.2 spatstat.geom_3.2-5
[133] Matrix_1.6-5 RcppHNSW_0.5.0
[135] patchwork_1.3.0.9000 future_1.33.0
[137] shiny_1.7.5.1 SummarizedExperiment_1.32.0
[139] ROCR_1.0-11 igraph_1.5.1 `