diff --git a/fileformats/medimage/__init__.py b/fileformats/medimage/__init__.py
index ef10886..7873030 100644
--- a/fileformats/medimage/__init__.py
+++ b/fileformats/medimage/__init__.py
@@ -36,9 +36,9 @@
     PetSinogram,
     PetCountRate,
     PetNormalisation,
-    Vnd_Siemens_PetRawData,
-    Vnd_Siemens_PetListMode,
-    Vnd_Siemens_PetSinogram,
-    Vnd_Siemens_PetCountRate,
-    Vnd_Siemens_PetNormalisation,
+    Vnd_Siemens_Biograph128Vision_Vr20b_PetRawData,
+    Vnd_Siemens_Biograph128Vision_Vr20b_PetListMode,
+    Vnd_Siemens_Biograph128Vision_Vr20b_PetSinogram,
+    Vnd_Siemens_Biograph128Vision_Vr20b_PetCountRate,
+    Vnd_Siemens_Biograph128Vision_Vr20b_PetNormalisation,
 )
diff --git a/fileformats/medimage/dicom.py b/fileformats/medimage/dicom.py
index 7231f3b..e57bd03 100644
--- a/fileformats/medimage/dicom.py
+++ b/fileformats/medimage/dicom.py
@@ -39,7 +39,6 @@ class DicomDir(DicomCollection, DirectoryContaining[Dicom]):
 
 
 class DicomSeries(DicomCollection, SetOf[Dicom]):
-
     @classmethod
     def from_paths(
         cls, fspaths: ty.Iterable[Path], common_ok: bool = False
@@ -47,7 +46,7 @@ def from_paths(
         dicoms, remaining = Dicom.from_paths(fspaths, common_ok=common_ok)
         series_dict = defaultdict(list)
         for dicom in dicoms:
-            series_dict[dicom["SeriesNumber"]].append(dicom)
+            series_dict[(str(dicom["StudyInstanceUID"]), str(dicom["SeriesNumber"]))].append(dicom)
         return set([cls(s) for s in series_dict.values()]), remaining
 
 
@@ -55,12 +54,16 @@ def from_paths(
 def dicom_collection_read_metadata(collection: DicomCollection) -> ty.Dict[str, ty.Any]:
     # Collated DICOM headers across series
     collated = copy(collection.contents[0].metadata)
-    if len(collection.contents) > 1:
-        for key, val in collection.contents[1].metadata.items():
-            if val != collated[key]:  # Turn field into list
-                collated[key] = [collated[key], val]
-    for dicom in collection.contents[2:]:
+    for i, dicom in enumerate(collection.contents[1:], start=1):
         for key, val in dicom.metadata.items():
             if val != collated[key]:
+                # Check whether the value is the same as the values in the previous
+                # images in the series
+                if (
+                    not isinstance(collated[key], list)
+                    or isinstance(val, list)
+                    and not isinstance(collated[key][0], list)
+                ):
+                    collated[key] = [collated[key]] * i + [val]
                 collated[key].append(val)
     return collated
diff --git a/fileformats/medimage/raw/__init__.py b/fileformats/medimage/raw/__init__.py
index 3a641e5..ac2e3b4 100644
--- a/fileformats/medimage/raw/__init__.py
+++ b/fileformats/medimage/raw/__init__.py
@@ -8,9 +8,9 @@
     PetSinogram,
     PetCountRate,
     PetNormalisation,
-    Vnd_Siemens_PetRawData,
-    Vnd_Siemens_PetListMode,
-    Vnd_Siemens_PetSinogram,
-    Vnd_Siemens_PetCountRate,
-    Vnd_Siemens_PetNormalisation,
+    Vnd_Siemens_Biograph128Vision_Vr20b_PetRawData,
+    Vnd_Siemens_Biograph128Vision_Vr20b_PetListMode,
+    Vnd_Siemens_Biograph128Vision_Vr20b_PetSinogram,
+    Vnd_Siemens_Biograph128Vision_Vr20b_PetCountRate,
+    Vnd_Siemens_Biograph128Vision_Vr20b_PetNormalisation,
 )
diff --git a/fileformats/medimage/raw/pet/__init__.py b/fileformats/medimage/raw/pet/__init__.py
index 316170d..14b8f70 100644
--- a/fileformats/medimage/raw/pet/__init__.py
+++ b/fileformats/medimage/raw/pet/__init__.py
@@ -6,9 +6,9 @@
     PetNormalisation,
 )
 from .siemens import (
-    Vnd_Siemens_PetRawData,
-    Vnd_Siemens_PetListMode,
-    Vnd_Siemens_PetSinogram,
-    Vnd_Siemens_PetCountRate,
-    Vnd_Siemens_PetNormalisation,
+    Vnd_Siemens_Biograph128Vision_Vr20b_PetRawData,
+    Vnd_Siemens_Biograph128Vision_Vr20b_PetListMode,
+    Vnd_Siemens_Biograph128Vision_Vr20b_PetSinogram,
+    Vnd_Siemens_Biograph128Vision_Vr20b_PetCountRate,
+    Vnd_Siemens_Biograph128Vision_Vr20b_PetNormalisation,
 )
diff --git a/fileformats/medimage/raw/pet/siemens.py b/fileformats/medimage/raw/pet/siemens.py
index 522feef..ee13e1d 100644
--- a/fileformats/medimage/raw/pet/siemens.py
+++ b/fileformats/medimage/raw/pet/siemens.py
@@ -7,30 +7,30 @@
 )
 
 
-class Vnd_Siemens_BiographVisionVr20b_PetRawData(PetRawData):
+class Vnd_Siemens_Biograph128Vision_Vr20b_PetRawData(PetRawData):
     iana_mime = None
     ext = ".ptd"
 
 
-class Vnd_Siemens_BiographVisionVr20b_PetListMode(
-    Vnd_Siemens_BiographVisionVr20b_PetRawData, PetListMode
+class Vnd_Siemens_Biograph128Vision_Vr20b_PetListMode(
+    Vnd_Siemens_Biograph128Vision_Vr20b_PetRawData, PetListMode
 ):
     pass
 
 
-class Vnd_Siemens_BiographVisionVr20b_PetSinogram(
-    Vnd_Siemens_BiographVisionVr20b_PetRawData, PetSinogram
+class Vnd_Siemens_Biograph128Vision_Vr20b_PetSinogram(
+    Vnd_Siemens_Biograph128Vision_Vr20b_PetRawData, PetSinogram
 ):
     "histogrammed projection data in a reconstruction-friendly format"
 
 
-class Vnd_Siemens_BiographVisionVr20b_PetCountRate(
-    Vnd_Siemens_BiographVisionVr20b_PetRawData, PetCountRate
+class Vnd_Siemens_Biograph128Vision_Vr20b_PetCountRate(
+    Vnd_Siemens_Biograph128Vision_Vr20b_PetRawData, PetCountRate
 ):
     "number of prompt/random/single events per unit time"
 
 
-class Vnd_Siemens_BiographVisionVr20b_PetNormalisation(
-    Vnd_Siemens_BiographVisionVr20b_PetRawData, PetNormalisation
+class Vnd_Siemens_Biograph128Vision_Vr20b_PetNormalisation(
+    Vnd_Siemens_Biograph128Vision_Vr20b_PetRawData, PetNormalisation
 ):
     "normalisation scan or the current cross calibration factor"