function [ RATINGS ] = GetRadiologistsRatings( data, rowNumber )

%GetRadiologistsRatings Collects radiologists ratings belonging to all the

%borders related to the same nodule image. 

%   Takes the location of the Excel file with the doctors semantic ratings,

%   and the name of the outline file you are interested in. Finds the name

%   of the source image, then collects the radiologists ratings for that

%   source image. Returns everything in the RATINGS structure. Easier than

%   using dicominfo('1.dcm') since we need the rating .xlsx or we're stuck

%   anyway. 

%   Gives the # of ratings, ID of source image, IDs of related border

%   images, and the ratings: subtlety,internalStructure,calcification,sphericity,

%   margin,lobulation,spiculation,texture,malignancy.

%modified column numbers 

%find how many ratings for this nodule 

noduleID = cell2mat(data(rowNumber,6));

i = 1;

while rowNumber+i <= size(data,1) && strcmp(cell2mat(data(rowNumber + i, 6)), noduleID) == 1

    i = i+1;

end

totalRatings = i;

matchingRows = (rowNumber:rowNumber + totalRatings - 1);

%1 subtlety, 2 calcification, 3 sphericity, 4 margin, 5 lobulation, 

%6 spiculation, 7 texture, 8 malignancy

RATINGS.totalRatings = totalRatings;

RATINGS.noduleID = noduleID;

RATINGS.relatedInstances = cell2mat(data(matchingRows, 1));

RATINGS.subtlety = cell2mat(data(matchingRows, 10));

RATINGS.calcification = cell2mat(data(matchingRows, 11)); %not a 'ranking' number

RATINGS.sphericity = cell2mat(data(matchingRows, 12));

RATINGS.margin = cell2mat(data(matchingRows, 13));

RATINGS.lobulation = cell2mat(data(matchingRows, 14));

RATINGS.spiculation = cell2mat(data(matchingRows, 15));

RATINGS.texture = cell2mat(data(matchingRows, 16));

RATINGS.malignancy = cell2mat(data(matchingRows, 17));

%RATINGS.internalStructure = cell2mat(data(matchingRows, 11)); %useless also not a ranking number

RATINGS.sourceID = RATINGS.noduleID(1:30);

RATINGS.sourceDirectory = char(data(matchingRows, 9)); %only need one of the identical entries

RATINGS.stdev = [std(RATINGS.subtlety), std(RATINGS.calcification), ...

    std(RATINGS.sphericity), std(RATINGS.margin), std(RATINGS.lobulation),...

    std(RATINGS.spiculation), std(RATINGS.texture), std(RATINGS.malignancy)];

RATINGS.rows = [rowNumber, rowNumber+totalRatings-1];

%Get borders in numerical form. 

borderCells = data(matchingRows, 21);

RATINGS.borders = ParseBorderCells(borderCells); 

RATINGS.area = cell2mat(data(matchingRows, 71));

%Get extrema from x,y coordinates in the borders

minCorner = min(RATINGS.borders{1}); %initialize

maxCorner = max(RATINGS.borders{1});

for i = 2:length(RATINGS.borders) %iterate

    minCorner = min([minCorner; RATINGS.borders{i}]);

    maxCorner = max([maxCorner; RATINGS.borders{i}]);

end

RATINGS.boundingBox = [minCorner; maxCorner];

end